A Thesis Submitted by R.SUMATHI. for the award of the degree of. DOCTOR OF PHILOSOPHY in COMPUTER SCIENCE AND ENGINEERING

Transcription

1 DEVELOPMENT AND ANALYSIS OF DISTINCT ENERGY-EFFICIENT ROUTING PROTOCOLS FOR LOAD BALANCING, SERVICE DIFFERENTIATION, QoS ASSURANCE AND LOCALIZATION IN WIRELESS SENSOR NETWORKS A Thess Submtted by R.SUMATHI for the award of the degree of DOCTOR OF PHILOSOPHY n COMPUTER SCIENCE AND ENGINEERING DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING Dr. M.G.R. EDUCATIONAL AND RESEARCH INSTITUTE UNIVERSITY (Declared U/S 3 of the UGC Act, 1956) CHENNAI NOVEMBER 2011

2 CERTIFICATE Certfed that ths thess ttled Development and Analyss of Dstnct Energy-Effcent Routng Protocols for Load balancng, Servce Dfferentaton, QoS Assurance and Localzaton n Wreless Sensor Networks, s the bonafde work of Mrs. R. SUMATHI who carred out the research under my supervson. Certfed further, that to the best of my knowledge the work reported heren does not form part of any other thess or dssertaton of the bass of whch a degree or award was conferred on an earler occason on ths or any other canddate. Dr. R. SRINIVASAN Professor, Dean Research & PG Studes Department of Computer Scence and Engneerng RNS Insttute of Technology, Bangalore Karnataka, Inda.

3 DECLARATION I declare that the thess enttled Development and Analyss of Dstnct Energy-Effcent Routng Protocols for Load Balancng, Servce Dfferentaton, QoS Assurance and Localzaton n Wreless Sensor Networks submtted by me for the award of degree of Doctor of Phlosophy s the record of work carred out by me durng the perod from November 2007 to November 2011 under the gudance of Dr. R. Srnvasan, Professor, Dean Research & PG Studes, Department of Computer Scence and Engneerng, RNS Insttute of Technology, Bangalore, Karnataka, Inda, and has not formed the bass for award of any degree, dploma, assocate-shp, fellowshp, ttles n ths or any other unversty or smlar nsttuton of hgher learnng. R. SUMATHI

4 ABSTRACT Wreless Sensor Network (WSN) s an emergng technology attractng sgnfcant research and commercal nterest. The basc components of WSN are small nodes wth sensng and wreless communcaton capabltes. The constant mprovements n dgtal crcut technology has made the deployment of such small, nexpensve, low-power, dstrbuted devces capable of nformaton gatherng, processng, and communcaton, a realty. Sensor nodes are constraned n energy supply and bandwdth. Such constrants combned wth a typcal deployment of large number of sensor nodes pose many challenges compared to tradtonal data routng n wred networks. Many energy effcent routng protocols are proposed that focus more on energy aware to maxmze the lfetme of the network. Conventonal energy effcent routng protocols are no longer capable to meet applcaton specfc servce and hence there s an mmedate need for newer routng protocols. Developng such routng protocols demand the adopton of routng servce akn to the applcaton specfc requrements such as: 1. Load balancng 2. Servce dfferentaton and 3. QoS assurance n terms of relablty and tmely delvery. To meet these routng servces, we propose three nnovatve type of protocols to be adopted n WSNs. They are: a. Load Balancng Dynamc Adaptve Routng (LBDAR) protocol b. Data Qualty Aware Routng (DQAR) protocol c. Energy Buffer Aware Relable Routng (EBARR) protocol The LBDAR s, a reactve protocol, developed to meet the load balancng servce n survellance applcatons. In these applcatons, networks are expected to operate over a longer perod of tme n an unattended and hostle envronment wth mnmal montorng. The LBDAR ensures the unform depleton of energy across the nodes, wth an objectve to ncrease the energy conservaton and prolong the lfetme of sensor nodes. The DQAR protocol s developed

5 to serve the applcatons where heterogeneous traffc s generated. The DQAR provdes servce dfferentaton wth an objectve to prortze and provde relablty assurance to hgh prorty packets compared to low and medum prorty packets. A novel energy effcent QoS aware routng protocol, EBARR, s proposed to provde QoS n tmelness and relablty domans for crtcal packets generated n tme crtcal applcatons. A unque archtecture s proposed to mplement the DQAR and EBARR protocols. Every sensor node wll have ths archtecture as part of ts operaton. In order to drect the flow of nformaton ether wth respect to hgh prorty or low prorty packets comng out of the proposed archtecture, from a partcular node to the next neghbor, t s mperatve that the next neghbor has to be dentfed. Ths necesstates the need for sutable localzaton algorthm. Locaton awareness s acheved prmarly by equppng the sensors wth GPS recevers, whch however, may be too expensve for the desred applcaton. Hence, alternatve soluton s to use a small number of anchor nodes n the network and are often heavy weght nodes, equpped wth GPS recever. The remanng nodes must determne ther poston relatve to the anchor nodes. But due to sparse deployment of sensor nodes or presence of obstacles, sensor nodes fal to get localzaton ether wth the help of GPS or anchor nodes. To handle such scenaro, a new range based, cost effectve Moble Anchor (MA) asssted localzaton technque s proposed n ths dssertaton to localze sensor node n two dmensonal spaces wth an objectve of mprovng localzaton accuracy. Approprate smulatons are conducted for every protocol and the results are plotted and compared wth exstng protocols. Graphcal representaton of comparsons reveals that the protocols presented by us have superor performance compared to some exstng protocols.

6 ACKNOWLEDGEMENTS I am very fortunate to be a Ph.D scholar of Dr. R. Srnvasan who has extraordnary knowledge n my area of research. I honestly and sncerely thank my gude and mentor, for acceptng me as hs student and provde valuable gudance and suggestons all through my research programme. I greatly admre hs atttude towards research, creatve thnkng, hard work and dedcaton. He has been a great source of nspraton to me n all my endeavors. The research work would not have been possble wthout hs bounteous effort. I take ths opportunty to record my grattude to Dr. M.G.R. Educatonal and Research Insttute, Chenna, for provdng me great nfrastructural facltes. I am hghly ndebted to the Vce-Chancellor and Dean Research, Dr. M.G.R. Educatonal and Research Insttute, Chenna, for ther knd cooperaton and support. I owe my nvaluable thanks to the Doctoral Commttee members Dr. S. Rav, Professor and Head of the Department of ECE, Dr.Cyrl Raj, Professor and Head of the Department of CSE and Dr. S.P. Raja Gopalan, Professor Emertus, Dr.M.G.R. Educatonal and Research Insttute, Chenna, for provdng nestmable comments, careful analyss and specfc constructve recommendatons to enhance the qualty of my research work. I acknowledge my parent nsttute Sddaganga Insttute of Technology, Prncpal and management for gvng me an opportunty to carry out my research work at Dr. M.G.R. Educatonal and Research Insttute, Chenna. My specal thanks goes to Dr. M.N. Channabasappa, Drector, for hs tmely motvaton and encouragement. I also thank the Head of the Department of CSE, colleagues and frends at Sddaganga Insttute of Technology for ther good wshes and support they extended durng my research work. I gratefully acknowledge Mrs. Malath w/o Dr. R. Srnvasan for her care and affecton to me and my famly throughout my research programme. My sncere thanks to my parents and famly members for moral support and encouragement rendered durng my research work.

7 TABLE OF CONTENTS Lst of Tables Lst of Fgures Lst of Symbols Lst of Abbrevatons xx 1 Introducton Wreless Sensor networks Communcaton archtecture Desgn factors Protocol stack archtecture Applcatons Routng n wreless sensor networks Routng challenges and desgn ssues Routng protocols objectves Classfcaton of routng protocols Localzaton n wreless sensor networks Localzaton challenges and desgn ssues Localzaton algorthm objectves Classfcaton of localzaton algorthms Organzaton of the thess 23 x x xv 2 Energy-Effcent Routng Protocols and Localzaton Algorthms: A Lterature survey Routng protocols Energy-effcent load balancng routng protocols Routng protocols for servce dfferentaton Routng protocols for relable and tmely delvery Localzaton algorthms Range-based schemes Range-free schemes Moble beacon-asssted schemes 40

8 v 3 Motvaton and objectve of the work Wreless sensor networks applcatons and routng Load balancng Servce dfferentaton Relable and tmely delvery Proposed routng protocols and ther objectves Localzaton and accuracy Proposed localzaton algorthm and ts objectves 47 4 Load Balancng Dynamc Adaptve Routng Protocol Models used Network model Energy model Traffc model Desgn approaches for load balancng Effcent selecton of next hop node Dynamc path exploraton Adaptable threshold energy settng and montorng Defntons LBDAR protocol Overvew Protocol descrpton Performance analyss Smulaton envronment Performance metrcs Results and dscusson Concluson 71 5 Data Qualty Aware Routng Protocol Network model Data model Structure of routng nformaton table Assumptons Table constructon mechansm QoS provsonng approaches n relablty doman 78

9 x 5.5 DQAR protocol Overvew Dfferentated servce at source nodes Dfferentated servce at ntermedate nodes Performance analyss Estmaton of response tme Estmaton of energy cost Smulaton Smulaton envronment Smulaton results and dscusson Concluson Energy-Buffer Aware Relable Routng Protocol Prelmnares QoS provsonng mechansms n relablty doman Need for buffer management Effcent proportonal buffer allocaton Effcent packet droppng polcy QoS provsonng n tmelness doman EBARR protocol Energy-Buffer Resource request (EBRreq) packet constructon Protocol overvew Operatons at Source Nodes Operatons at Intermedate Nodes Performance analyss Assumptons Evaluatng packet loss of flow f at IN Evaluatng the servce delay of flow f at IN Smulaton Smulaton Envronment Performance metrcs Results and dscusson Concluson 136

10 x 7 Moble Anchor Asssted Localzaton Algorthm System envronment and assumptons Moble Anchor trajectory Beacon message Beacon nterval Vstor nterval Dstance calculaton usng RSSI MAAL Algorthm Beacon message collecton Dstance computaton Locaton estmaton Performance analyss Smulaton envronment and parameters Performance metrcs Smulaton results and dscusson Implementaton ssues Concluson Concluson 155 Appendx References Lst of publcatons Vtae

11 LIST OF TABLES 4.1 Neghbor lst of sensor node Smulaton parameters Comparson of energy effcency and packet delvery rato Smulaton results of standard devaton of resdual energy Angle Based Router Informaton Table (ABRIT) Smulaton parameters Lst of tme parameters Moble Anchor Locaton Table (MALT) Smulaton parameters Tme complexty of matrx operatons 154

12 LIST OF FIGURES 1.1 A typcal WSN deployed n forest to montor events WSN communcaton archtecture A Classfcaton of WSN desgn ssues Archtecture of sensor node The WSNs protocol stack Overvew of WSN applcatons Routng protocols n WSNs: a taxonomy A typcal wreless sensor network model An llustraton of creaton of holes n WSN Illustraton of dynamc path exploraton for every new data ntaton at source nodes 4.4 Format of IMP Format of NIP Format of IRP Format of ICT A Graph of sensor nodes llustratng IRP floodng and dynamc path exploraton 4.9 Format of data packet Average remanng energy vs. packet generaton rate Packet delvery rato vs. packet generaton rate Network lfetme vs. ntal energy Standard devaton of resdual energy vs. node densty Standard devaton of frequency count vs. node densty

13 x 5.1 A typcal wreless sensor network model Illustraton of constructon of RIT and ABRIT at node v 1, v 2, and v 3 n a sensor network model 5.3 Constructon of ABRIT at each node based on specfed angle Illustraton of establshment of multple path n the optmal path regon Illustraton of dynamc multpath exploraton for every newly ntated traffc Illustraton of hop-by-hop uncastng wth request-reply message exchange 5.7 Illustraton of pre-establshed multpath sharng common router Packet schedulng and servcng Illustraton of exploraton of multple paths for HPD packets and devaton of path from optmal regon for LPD and MPD packets 5.10 Illustraton of hop-by-hop uncastng wth energy reservaton Format of ERREQ packet Format of Data packet Proposed archtecture at ntermedate nodes to provde dfferentated servces 5.14 A Queueng model at Intermedate Node M/G/1 Queueng model wth three prorty levels Illustraton of energy reservaton mechansm before transmttng crtcal data flow f at each IN 5.17 Relablty vs. packet arrval rate Packet loss due to collson vs. packet arrval rate Average remanng energy vs. packet arrval rate Average delay vs. packet arrval rate Relablty vs. node falure probablty Average packet delay vs. node falure probablty A hgh heterogeneous traffc at an ntermedate node

14 xv 6.2 Repercussons of buffer overflow at an ntermedate node An llustraton of multple flows wth dfferent prorty and data sze at IN Format of EBRreq packet Illustraton of dynamc multpath exploraton for every newly ntated data transmsson at SN 6.6 Illustraton of energy and buffer reservaton usng hop-by-hop uncastng wth request-reply polcy 6.7 Archtecture of source node Format of data packet Proposed IN archtecture to provde dfferentated servce A sample network consstng k number of sources generatng m number of dfferent prorty flows 6.11 Message transton dagram at ntermedate nodes Requred relablty vs. reportng rate Hgh prorty packet loss due to buffer overflow vs. reportng rate Hgh prorty packet loss due to packet collsons vs. reportng rate Average energy consumpton vs. reportng rate Average end-to-end delay vs. reportng rate Network lfetme vs. ntal energy 134 Requred relablty vs. reportng rate for dfferent buffer szes, B n 6.18 bytes 6.19 Hgh prorty packet loss due to buffer overflow vs. reportng rate for dfferent buffer szes, B n bytes 7.1 A typcal WSN wth sngle MA and unknown nodes Moble Anchor trajectory Format of beacon message Beacon message collecton Estmaton of dstance from unknown node to beacon message pont

15 xv 7.6 Locaton error vs. beacon nterval Locaton error vs. rado range Localzaton rato vs. rado range Illustraton of convergence accuracy Localzaton rato as functon of node densty Dependence of convergence accuracy on movng speed of MA node 153

16 LIST OF SYMBOLS A A square sensng network area G { v, E} A graph conssts of set of vertces and edges S SN V IN v r * Av Set of source nodes Source node Set of ntermedate nodes Intermedate node Snk node Rado transmsson range of node Area of the rado range of node v. d IN, IN ) Dstance between node IN and INj and gven by 2-D Eucldean dstance ( j RSAv Router Set Area of IN v V L v ABRSv Routng angle Drect path between node v and snk v * Angle Based Router Set of node v f Informaton flow generated at SN R f Relablty of flow f f N rec f N sent f N loss Number of packets receved at the snk Number of packets sent by the source Loss of packets at IN X Servce tme random varable for flow of prorty R Resdual servce tme random varable for flow of prorty W Arrval rate for flow of prorty (Posson arrvals) Utlzaton of the server by flow of prorty Random varable for the tme a flow of prorty spends watng from arrval untl servce begns

17 xv N T f E cos t Random varable for the number of packets n queue (not countng jobs for whch servce has already begun) Random varable for the tme a flow of prorty spends n the system from arrval untl the completon of servce Energy cost factor W Watng tme of flow f n queue C Completon tme of current prorty flow T Response tme of flow f at IN E Tx ( k, d) Energy requred to transmt a k -bts message over dstance d ERx E elec DS amp Energy to receve the data message: Amount of energy, rado dsspates to run the transmtter or recever crcutry Amount of energy to run transmtter amplfer Sensed data sze Amount of energy requred to transmt and receve k bt of message over E tot ( k, d) dstance d. DS Ereq Ecurrent Ethsh Energy requre to transmt data of sze DS Current energy level at a gven node Threshold energy at a gven sensor node E mn Mnmum energy at a gven sensor node Eaval e Eres res f FC FC Avalable energy at a gven node Standard devaton of resdual energy Resdual energy at node Mean resdual energy Standard devaton of frequency Count Frequency count at node Mean frequency count x y ( v, v ) Represents the x-y locaton of IN V N( v 1 ) Neghbor set of IN v 1 v

18 xv r ( v, v j ) B b Relablty of the hop between IN v andv on path p Buffer free space Number of buffer locatons f ( DS ) Data sze of flow R f f The rato of the number of packets arrved at the snk to the number of packets generated at the source SN f T Servce delay of flow f ser at source f P Packet loss probablty of flow f loss f P Bufloss f p Engdep SN Probablty of loss of packets due to buffer overflow of allocated buffer for flow f Probablty of loss of packets due to depleton of reserved energy e ( f ) Energy consumpton for flow P l Prorty level f t _ EBRreq packet arrval tme req arr f t _ EBRreq packet servcng tme req ser f t _ EBRreq packet forwardng tme req for f j b f t req _ prop f t data _ arr f t data_ ser f t buf _ wat f t buf _ res f t eng _ res f t send_ ack f t rec_ ack f t ack _ prop ( T 1 T ) EBRreq packet propagaton tme Data packet arrval tme Data packet servcng tme Data packets watng tme n allocated buffer Buffer reservaton tme Energy reservaton tme Acknowledgement sendng tme Acknowledgement recepton tme Acknowledgement propagaton tme Beacon nterval t

19 xx B t p r p k r dˆ n Beacon poston Transmtted power Receved power Propagaton constant Envronmental factors that affect the receved power Dstance between unknown node and MA node Dstance computed usng receved sgnal strength Dstance measurement error

20 LIST OF ABBREVIATIONS ABRIT ADC Aerr/Ardy AH AOA BM BMP BST DCF DFU DQAR DVU EBARR EBRreq EC ERQUEUE ERREQ ERU FC FCFS GPS Angle Based Router Informaton Table Analog to Dgtal Converter Acknowledgement error / Acknowledgement ready Acknowledgement Handler Angle of Arrval Buffer Manager Beacon Message Pont Buffer Status Table Dstrbuted Coordnated Functon Data packet Forwardng Unt Data Qualty Aware Routng Duplcate Verfer Unt Energy-Buffer Aware Relable Routng Energy-Buffer Resource request Energy Comparator Energy Request QUEUE Energy Reservaton REQuest Energy Reservaton Unt Frequency Count Frst Come Frst Serve Geographcal Postonng System

21 xx HELLO_PKT HPD HPRIT ICT IMP INs IRP LBDAR LPD LRR MA MAAL MAC MALT MANET S MEMS MLQ MPD NIP NL NS-2 PAL PDP PFA PFU Hello Packets Hgh Prorty Data Hgh Prorty Router Informaton Table Interest Cache Table Interest Message Packet Intermedate Nodes Interest Request Packet Load Balancng Dynamc Adaptve Routng Low Prorty Data Least Recent Removal Moble Anchor Moble Anchor Asssted Localzaton Medum Access Control Moble Anchor Locaton Table Moble Ad-hoc NETworks Mcro Electro Mechancal Systems Mult Level Queue Medum Prorty Data Node Informaton Packet Neghbor Lst Network Smulator-2 Proportonal Allocaton polcy Packet Droppng Polcy Packet Forwardng and Analyzer Packet analyzer and Forwardng Unt

22 xx QoS RIT RPU RRE RRP. RRR RRT RRU RSA RSSI RSU SNs TDOA TOA WSNs Qualty of Servce Router Informaton Table Request packet Processng Unt Route Request Error Round Robn Ponter Route Request Ready Relablty Requrement Table Resource Reservaton Unt Router Set Area Receved Sgnal Strength Indcaton Router Selecton Unt Source Nodes Tme Dfference of Arrval Tme of Arrval Wreless Sensor Networks

23 CHAPTER 1 INTRODUCTION 1.1 Wreless Sensor Networks Wth the recent technologcal advances n the area of wreless communcatons, processor, memory, rado, low power and hghly ntegrated dgtal electroncs and Mcro Electro Mechancal Systems (MEMS) [1], t becomes possble to sgnfcantly develop tny and small sze, low power, and low cost multfunctonal sensor nodes. These nodes whch consst of sensng, data processng, and communcatng components, leverage the dea of Wreless Sensor Networks (WSNs) based on collaboratve effort of large number of such nodes. A WSN s a network that s made up of hundreds or thousands of sensor nodes whch are densely deployed ether nsde the phenomenon or very close to t. The poston of sensor nodes need not be engneered or pre-determned, so that t leads to random deployment n naccessble terrans or dsaster relef operatons. On the other hand, ths poses a challenge that sensor network protocols and algorthms must possess self-organzng capabltes. Sensor nodes wth an embedded processor use ther processng abltes to locally carry out smple computatons and transmt only the requred and partally processed data, nstead of sendng raw data to the nodes whch are responsble for the fuson. Sensor networks represent a new paradgm n data collecton, when they are deployed n the followng two ways [2]:

24 2 Sensors can be postoned far from the actual phenomenon,.e., somethng known by sense percepton. In ths approach, large number of sensors, whch use some technques to dstngush targets from envronmental nose, are requred. Several sensors that perform only sensng can be deployed. The postons of the sensors and communcatons topology are carefully engneered. They transmt tme seres of the sensed phenomenon to the central nodes where computatons are performed and data are fused. As an llustraton, a WSN deployed n forest to montor events s shown n Fgure 1.1. Fgure 1.1: A typcal WSN deployed n forest to montor events Some of the mportant goals of a WSN are to: ) determne the value of physcal varables at a gven locaton, ) detect the occurrence of events of nterest, and estmate parameters of the detected event(s), ) classfy a detected object, and v) track an object. A WSN may consst of dfferent types of sensors such as sesmc, magnetc, thermal, vsual, nfrared, acoustc and radar, whch are able to montor a wde varety of ambent condtons such

25 3 as [3] temperature, humdty, vehcular movement, lghtnng condton, pressure, sol makeup, nose levels, the presence or absence of certan knds of objects, mechancal stress levels on attached objects, and the current characterstcs such as speed, drecton, and sze of an object. WSNs vs. MANETs MANETs (Moble Ad-hoc Networks) and sensor networks are two classes of the wreless adhoc networks wth resource constrants. MANETs typcally consst of devces that have hgh capabltes, moble and operate n coaltons for dsaster management applcatons. WSNs are typcally deployed n specfc geographcal regons for trackng, montorng and sensng. Both these wreless networks are characterzed by ther adhoc nature that lack predeployed nfrastructure for computng and communcaton. Both share some characterstcs lke dynamc network topology, power constrant and wreless communcaton between the nodes. Some of the fundamental dfferences between MANETs and WSNs are: Sensor networks are manly used to collect nformaton whle MANETS are desgned for dstrbuted computng rather than nformaton gatherng. Sensor nodes manly use broadcast communcaton paradgm whereas most MANETs are based on pont-to-pont communcatons. The number of nodes n sensor networks can be several orders of magntude hgher than that n MANETs. Sensor nodes may not have global dentfcaton (ID) because of the ncreased overhead of address management. Sensor nodes are much cheaper than nodes n a MANET and are usually deployed n thousands. Sensor nodes are lmted n power, computatonal capactes, and memory where as nodes n a MANET can have more resources. Usually, sensors are deployed once n ther lfetme, where as n MANET, nodes can be dynamcally deployed on demand. Sensor nodes are much more lmted n ther computaton and communcaton capabltes than ther MANET counterparts due to ther low cost.

26 Communcaton archtecture One of the most mportant constrants on sensor nodes s the low power consumpton requrement. Sensor nodes carry lmted, generally rreplaceable power sources; hence t s very mportant to make effcent use of battery power n order to ncrease the lfetme of network. In partcular, most of the energy of sensors s spent n transmsson of data. So, WSNs use multhop communcaton for data transmsson, whch consumes less power than the tradtonal sngle hop communcaton. Furthermore, the transmsson power levels can be kept low, whch s hghly desred n covert operatons. Multhop communcaton can also effectvely overcome some of the sgnal propagaton effects experenced n long-dstance wreless communcaton. The communcaton archtecture for WSN s shown n Fgure 1.2.The man enttes that buld the archtecture are [4] lsted below: Snk Sensor node Sensor feld User Event Fgure 1.2: WSN communcaton archtecture The sensor node s man objectves are makng dscrete local measurement of surroundng phenomenon, formng a network by communcatng over a wreless medum and data acquston and then route data back to the user va snk (Base Staton). The snk communcates wth the user va nternet or satellte communcaton. It s located near the sensor feld or well-equpped nodes of the sensor network.

27 5 Phenomenon s an entty of nterest to the user to collect measurements about. Ths phenomenon s sensed and analyzed by the sensor nodes. The user s the one who s nterested n obtanng nformaton about specfc phenomenon to measure/montor ts behavor Desgn factors Varous factors essental for desgn and deployment are classfed on the bass of four enttes, namely: 1. Sensor node resources 2. Sensor network topology 3. Communcaton model and 4. Montored data (Fgure1.3) WSN desgn ssues Sensor nodes constrants Sensor Network topology Communcaton model Montored data Relablty Power consumpton Hardware constrants Scalablty Self confguraton Securty Network Dynamcs Transmsson meda Coverage Connectvty Fgure 1.3: A Classfcaton of WSN desgn ssues Data fuson Qualty of Servce. Sensor node resources: A WSN desgn s nfluenced by several sensor node resources whch nclude lmted memory, energy and hardware constrants. Relablty: Some sensor nodes may fal or be blocked due to lack of power, physcal damage or envronmental nterference. The falure of sensor nodes should not affect the overall task of the sensor network. Ths s the relablty or fault tolerance ssue. Fault tolerance s the ablty to sustan functonaltes of sensor network wthout any nterrupton due to node falures [5, 6, 7].

28 6 The relablty or fault tolerance of a sensor node s modeled n [5] usng the Posson dstrbuton to capture the probablty of not havng a falure wthn the tme nterval (0, t): R ( t) exp( t) k k Where k and t are the falure rate of sensor node k and the tme perod, respectvely. Power Consumpton: One of the components of sensor nodes s the power source whch s very lmted. The node s battery-operated and hence the lfe tme of a sensor node depends strongly on the battery lfe tme, especally where no power source replenshment s possble n some applcaton scenaros. Snce the man objectves of sensor nodes are sensng/collectng events, data processng, and data transmsson through routng, the power resource can be dvded among these three operatons (sensng, computaton, and communcatons). On the other hand, lfetme of a sensor node plays a key role on energy effcency and robustness of the node and so many researchers are focusng on desgnng power-aware protocols and algorthms for WSN wth the goal of mnmzaton of energy expendture [8, 9,10]. Hardware constrants: Fgure 1.4 shows four basc components of a sensor node: sensor unt, processng unt, transcever unt and power unt. It may also have applcaton dependent addtonal components such as locaton fndng system, power generator and a moblzer. Sensor unts are usually composed of two subunts: sensors and analog to dgtal converters (ADCs). Locaton fndng system Moblzer Sensor unt Sensor ADC Processng unt Processor Storage Transcever Power Unt Power Generator Fgure 1.4: Archtecture of sensor node

29 7 The analog sgnals produced by the sensors based on the observed phenomenon are converted to dgtal sgnals by the ADC, and then fed nto the processng unt. The processng unt, whch s generally assocated wth a small storage unt, manages the procedures that make the sensor node to collaborate wth the other nodes and carry out the assgned sensng tasks. A transcever unt connects the node to the network. One of the most mportant components of a sensor node s the power unt. Power unts may be supported by a power generatng unt such as solar cells. There are other subunts too whch are applcaton dependent.. Sensor network topology Sheer number of naccessble and unattended sensor nodes, whch are prone to frequent falures, make topology mantenance a challengng task. Hundreds to several thousands of nodes are deployed throughout the sensor feld at a densty of about 20 nodes/m 3 [11]. Deployng hgh number of nodes requres careful handlng of topology mantenance. Followng are the ssues related to topology mantenance: Scalablty: The number of sensor nodes deployed n studyng a phenomenon may be n the order of hundreds or thousands. The densty of these nodes affect the degree of coverage area of nterest. The network sze affects relablty, accuracy, and data processng algorthms [10]. The densty can range from a fewer sensor nodes to a hundred n a regon that can be less than 10m n dameter. The densty s calculated as n [12]: ( R ) ( N R ) / A Where N s the number of scattered sensor nodes n regon A, and R s the rado transmsson range. (R) gves the number of nodes wthn the transmsson radus of each node n regon A. 2 Self-Confguraton: It s essental for WSN to be self-organze, snce the densely deployed sensor nodes n a sensor feld may fal due to many reasons lke lack of energy, physcal destructon, envronment nterference, communcatons problem, nactvty etc. and new nodes may jon the network. On the other hand, sensor nodes are unattended n a dynamc envronment; so nodes need a self-confguraton technque to establsh a topology that supports

30 8 communcatons under severe energy constrants. It s worthy to menton that self-confguraton n WSN s an essental factor to mantan the functons properly and serve ts purpose [13,14]. Network dynamcs: In many applcatons, the movement of sensor nodes or the base staton (snk) s essental. Ths means that sensor nodes can have moblty factor. (.e.,not statonary as assumed by many of network archtectures). Ths has arsen the routng stablty ssues as well as energy avalablty, bandwdth, etc. Moreover, the specfc sensed phenomenon may be ether dynamc (e.g., target detecton/ trackng applcatons) or statonary (e.g., forest montorng) dependng on the applcatons. Securty: Securty aspects n WSNs have been focused on the centralzed communcatons approaches. Some of the threats to a WSN are descrbed n [15,16,17] and categorzed as follows: Passve Informaton Gatherng, False Node, Node Outage, Supervson of a Node, Node Malfuncton, Message Corrupton, Denal of Servce, and Traffc Analyss. There s a need to develop dstrbuted securty approaches for WSN.. Communcaton model Transmsson Meda: In a mult-hop sensor network, a wreless medum s used to lnk nodes for communcaton purpose. These lnks can be formed by rado (e.g., Bluetooth compatble 2.4 GHz transcever), Infrared whch s lcense free and robust to nterference from electrcal devces, and Optcal meda. Coverage: The sensor node s vew of the envronment s lmted both n range and n accuracy. Ths means that the ablty of sensor nodes to cover physcal area of the envronment s lmted [10, 18]. Connectvty: A permanent connecton between any two ndvdual sensor nodes that are densely deployed n a sensor feld defnes the network connectvty. The connectvty s of great mportance, snce t nfluences communcatons protocols desgn and data dssemnaton technques. Also, t s worth mentonng that connectvty of sensor network does not prevent the

31 9 network topology from beng varable and the network sze from reducton as a result of the death or falure of some sensor nodes due to the reasons mentoned earler. v. Montored data Data Aggregaton/Data Fuson: It s the task of reducng data sze by summarzng the data nto a set of meanngful nformaton va computaton durng data transmsson. As sensor networks are made of large number of sensor nodes, ths can easly congest the network by floodng t wth nformaton [19]. Hence, a soluton to data congeston n sensor networks s to use computaton to aggregate or fuse data wthn WSN, then transmt only the aggregated data to the controller. Qualty of Servce: For some applcatons, data delvery wthn a bounded latency (.e., tme constraned applcatons) s of great mportance; otherwse, the sensed data that delvered after certan latency wll be useless. In other applcatons (e.g., not tme-constraned applcatons), the conservaton of power s more mportant than the qualty of the sent data. So, there s a trade off between the qualty of servce/the qualty of data sent and the energy conservatons or consumpton dependng on the applcatons [20, 21] Protocol stack archtecture The archtecture of protocol stack [8] used by the snk and sensor nodes s shown n Fgure 1.5. The protocol stack ntegrates power and routng awareness (.e., energy-aware routng), ntegrates data wth networkng protocols (.e., data aggregaton), communcates power effcently through the wreless medum, and promotes cooperatve efforts of sensor nodes (.e., task management plane). Ths protocol stack comprses of physcal layer, data lnk layer, network layer, transport layer, applcaton layer, power management plane, moblty management plane, and task management plane. The physcal layer addresses the needs of a robust modulaton, transmsson and recevng technques. The network layer takes care of routng the data suppled by the transport

32 10 layer. The transport layer mantans the flow of data f the WSN applcaton requres t. Dependng on the sensng tasks, dfferent types of applcaton software can be set up and used n the applcaton layer. Applcaton layer Transport layer Network layer Data Lnk layer Physcal layer Task Management plane Moblty Management plane Power Management plane Fgure 1.5: The WSNs protocol stack The power management plane manages how a sensor node uses ts power and manages ts power consumpton among the three operatons (sensng, computaton, and wreless Communcatons). The moblty management plane detects and regsters the movement/ moblty of sensor nodes as a network control prmtve. The task management plane (.e., cooperatve efforts of sensor nodes) balances and schedules the event s sensng and detectng tasks from a specfc area Applcatons WSNs are appled to wde range of applcatons [22, 23, 24] and these applcatons can be classfed nto two categores: montorng and trackng as shown n Fgure 1.6. Montorng applcatons nclude ndoor/outdoor envronmental montorng, health montorng, power montorng, nventory locaton montorng, factory and process automaton, and sesmc and structural montorng. Trackng applcatons nclude trackng objects, anmals, humans, and vehcles. The dea behnd these applcatons s that, densely deployng sensor nodes wth

33 11 capabltes of sensng, wreless communcatons, and computaton n an unattended envronment, wll assst n measurng ts ambent condtons, and obtanng the characterstcs about phenomenon of nterest surroundng these sensors, by transformng these sensed/gathered data nto electrcal sgnals that can be processed. WSN Applcatons Trackng Applcatons Montorng Applcatons Mltary Enemy trackng Habtat Anmal trackng Mltary Securty detecton Habtat Anmal montorng (zebra, brds etc) Publc (Traffc trackng) Industry and Busness (Human trackng) Busness (Inventory montorng) Health Patent montorng Publc\Industral Structural montorng Factory montorng Inventory montorng Machne montorng Chemcal montorng Envronment Envronmental montorng (weather, temperature, pressure) Home networks Home applances montorng Fgure 1.6: Overvew of WSN applcatons 1.2 Routng n wreless sensor networks Routng n WSNs s a challengng task due to the nherent characterstcs that dstngush these networks from other wreless networks lke moble ad hoc networks or cellular networks and many solutons have been developed to address ths problem. Ensurng effcent routng, faces many challenges due to both wreless communcaton effects and the peculartes of sensor networks. These challenges preclude exstng routng protocols developed for wreless ad hoc networks from beng used n WSNs. Instead, novel energy effcent routng protocols are requred. Some of the mportant challenges n WSNs are descrbed n the followng subsectons.

34 Routng challenges and desgn ssues Energy resource: The man objectve of the routng protocols s effcent delvery of nformaton between sensors and the snk. To ths end, energy consumpton s the man concern n the development of any routng protocol for WSNs. Because of the lmted energy resources of sensor nodes, data needs to be delvered n the most energy-effcent manner wthout compromsng the accuracy of the nformaton content and so energy consumpton should be carefully nvestgated and new energy-effcent routng protocols are developed for WSNs. Node falure: WSNs rely on the nodes nsde the network to delver data n a mult-hop manner. Hence, routng protocols operate on these sensor nodes nstead of dedcated routers such as n the Internet. The low cost components used n sensor nodes, however, may result n unexpected falures to such an extent that the sensor node may be non-operatonal. Moreover, the wreless channel results n packet losses durng communcaton. Thus routng protocols should provde robustness to node falures and prevent sngle pont-of-falure stuatons, where the nformaton s lost f a sensor des. Even under very harsh condtons wth frequent channel errors and node falures the routng protocol should provde effcent delvery between the sensor and the snk. Dynamc network topology: The deployment of a WSN can be ether predetermned or through a random strategy. Whle predetermned topology can be exploted to desgn more effcent routng protocols, ths s usually not the case for WSNs. Consequently, ndvdual nodes are usually unaware of the ntal topology of the network. However, the relatve locatons of the neghbors of a node and the relatve locaton of the nodes n the network sgnfcantly affect the routng performance. Therefore, routng protocols should provde topology-awareness such that the neghborhood of each node s dscovered and the routng decsons are made accordngly. Furthermore, the network topology can change dynamcally durng the lfetme of the network. Snce energy effcency s crucal, nodes may swtch off the transcever crcutry, whch, n effect, results n removng a node from the topology. Whenever the node s actve agan, t jons the network. These changes between actve and sleep states of nodes dynamcally affect the neghborhood topology of a sensor node.

35 13 Node moblty: WSN topology s usually assumed to be statc. However, dynamc changes due to snk moblty or target moblty can affect the communcaton structure and hence the routes. Consequently, the routng protocol should also be adaptve to these changes. Data heterogenety: Some applcatons of sensor networks mght requre a dverse mxture of sensor nodes of dfferent types and capabltes. Data from dfferent sensors can be generated at dfferent rates, the network can follow dfferent data reportng models and can be subjected to dfferent qualty of servce constrants. Such a heterogeneous envronment makes routng more complex. Communcaton overhead: Many routng protocols requre every node to exchange nformaton between ts neghbors. The nformaton to be exchanged can vary accordng to the routng technques. Whle most geographcal routng protocols requre knowledge of the locatons of the neghbor nodes, a data-centrc protocol may requre the nformaton content of the observed values of each sensor n ts surroundng. In each case, nodes consume energy n exchangng ths nformaton through the wreless medum, whch ncreases the overhead of the protocol. In order to mprove the energy effcency of the routng protocols, local nformaton exchange should be mnmzed wthout hamperng the routng accuracy. Node densty: The need to observe physcal phenomena n detal may requre a hgh-densty deployment of sensor nodes. Large number of nodes prevents global knowledge of the network topology from beng obtaned at each node. Hence fully dstrbuted protocols whch operate wth lmted knowledge of the topology, need to be developed to provde scalablty. Furthermore, snce hgh-level nformaton s more mportant than ndvdual peces of nformaton from each sensor node, the routng protocol should support n-network combnaton of the nformaton from a large number of nodes wthout hamperng energy consumpton. Addressng: Large number of sensor nodes n a network prevents unque addresses from beng assgned to each node. Whle local addressng mechansms can stll be used to facltate communcaton between neghbors, address-based routng protocols are not feasble because of the large overhead requred to use unque addresses for each communcaton. Consequently, the

36 14 majorty of the ad hoc routng protocols cannot be adopted for WSNs snce these solutons requre unque addresses for each node n the network. Furthermore, users are nterested n collectve nformaton from multple sensors regardng a physcal phenomenon nstead of nformaton from ndvdual sensors, and hence new addressng mechansms or novel routng technques that do not requre unque IDs for each node, are requred. Applcaton: The type of applcaton s also mportant for the desgn of routng protocols. In montorng applcatons, usually nodes communcate ther observatons to the snk n a perodc manner. As a result, statc routes can be used to mantan effcent delvery of the observatons throughout the lfetme of the network. In event-based applcatons, however, the sensor network s n sleep state most of the tme. However, whenever an event occurs, routes should be generated to delver the event nformaton n a tmely manner. Moreover, event locaton s not fxed snce t s drectly related to the event and so new routes should be generated for each event. It can be seen that the routng technque s drectly related to applcaton and sgnfcantly dfferent technques may be requred for dfferent knds of applcatons Routng protocols objectves In WSNs, data delvery servce of routng protocols s applcaton dependent. Some sensor applcatons only requre the successful delvery of messages between source and destnaton. However, there are applcatons that need even more assurance and hence, t s necessary to develop routng protocols dependng on applcaton requrement. Followng are varous objectves of the routng protocols: Data assurance: The assurance of message delvery s ndspensable for all routng protocols. It means that the protocol should always fnd the route between the communcatng nodes, f t really exsts. Ths correctness property can be proven n a formal way, whle the average-case performance can be evaluated by measurng the message delvery rato. Qualty of servce: Some real tme applcatons requre that a crtcal data must be delvered to base staton more relably wthn a specfed tme so that mmedate remedal and defensve

37 15 acton can be taken. Therefore, power constraned sensor networks for real tme applcatons have demanded energy and QoS routng protocol to delver the crtcal data wth low latency and hgh relablty. Thus QoS routng s an mportant topc n sensor network research and t has been under the focus of the research communty of WSNs. Mtgate packet loss: In some sensor network applcatons, the detecton accuracy of the event s dependent on data delvery rato. The data delvery rato s defned as the rato of number of packets successfully receved by the snk to the number of packets generated by source nodes. As delvery rato decreases below the specfed level, the detecton accuracy of an event become lower at the snk and affects the network responsveness. Hence, t s necessary to control packet loss at each hop. The reasons for data or packet loss n WSNs are collson between transmttng nodes, congeston, buffer overflows at relay nodes, envronmental dsturbances, dead nodes, moble nodes and human nterference. Therefore, t necessary to develop routng protocol whch mtgate the packet loss. Load balancng and Network lfetme: Ths protocol objectve s crucal for those networks, where the applcaton must run on sensor nodes as long as possble. The protocols, amng ths concern, try to balance the energy consumpton equally among nodes consderng ther resdual energy levels. However, the metrc used to determne the network lfetme s also applcaton dependent. Most protocols assume that every node s equally mportant and they use the tme untl the frst node des as a metrc, or the average energy consumpton of the nodes as another metrc. If nodes are not equally mportant, then the tme untl the last or hgh-prorty nodes de can be a reasonable metrc. Dfferentated servces: A WSN may ncorporate heterogeneous applcatons and all the deployed sensor nodes may have multple sensors.e. lght, temperature, sesmc etc. Data generated wth each applcaton has dfferent prorty, characterstcs and requrements n terms of relablty and delvery. Hence, to ensure desred relablty for each type of data based on the gven prorty, t s necessary to develop routng protocol whch provdes dfferentated servce at each node.

38 Classfcaton of routng protocols In general, routng n WSNs can be dvded nto flat routng, herarchcal routng, and locaton-based routng dependng on the network structure. In flat routng, all nodes are typcally assgned equal roles or functonalty. In herarchcal routng, nodes wll play dfferent roles n the network. In locaton-based routng, sensor node s postons are exploted to route data n the network. A routng protocol s consdered adaptve f certan system parameters can be controlled n order to adapt to the current network condtons and avalable energy levels. Furthermore, these protocols can be classfed nto multpath-based, query-based, negotatonbased, QoS-based, or coherent-based routng technques dependng on the protocol operaton. In addton to the above, routng protocols can be classfed nto three categores, namely, proactve, reactve, and hybrd protocols dependng on how the source fnds a route to the destnaton. In proactve protocols, all routes are computed before they are really needed, whle n reactve protocols, routes are computed on demand. Hybrd protocols use a combnaton of these two deas. When sensor nodes are statc, t s preferable to have table drven routng protocols rather than usng reactve protocols. A sgnfcant amount of energy s used n route dscovery and setup of reactve protocols. Another class of routng protocols s called the cooperatve routng protocols. In cooperatve routng, nodes send data to a central node where data can be aggregated and may be subject to further processng and hence reducng route cost n terms of energy use. Many other protocols rely on tmng and poston nformaton. The classfcaton s shown n Fgure 1.7. Routng protocols n WS Ns Network structure Protocol operaton Flat network routng Herarchcal network routng Locatonbased routng Negotaton- Based routng Multpath- Based routng Querybased routng QoS- Based routng Coherentbased routng Fgure 1.7: Routng protocols n WSNs: a taxonomy

39 Localzaton n wreless sensor networks Locaton dscovery n sensor networks has been an actve research area for the past couple of years and many applcatons are beng developed n ths area. The problem of estmatng spatal coordnates of a sensor node n a WSN s referred to as localzaton. Locaton nformaton also supports many fundamental network servces, ncludng network routng, topology control, coverage, boundary detecton, clusterng, etc. A bref overvew of the need of localzaton n realzng these servces s dealt wth as shown below. Routng: Most routng protocols for mult-hop wreless networks utlze physcal locatons to construct forwardng tables and delver messages to the node closer to the destnaton n each hop[25]. Specfcally, when a node receves a message, local forwardng decsons are made accordng to the postons of the destnaton and ts neghborng nodes. Such geographc routng schemes requre localzed nformaton, makng the routng process stateless, scalable, and lowoverhead n terms of route dscovery. Topology Control: Topology control s one of the most mportant technques used n wreless adhoc and sensor networks for savng energy and elmnatng rado nterference [26, 27]. By adjustng network parameters (e.g., the transmttng range), energy consumpton and nterference can be effectvely reduced. Meanwhle some global net-work propertes (e.g., connectvty) can stll be well retaned. Importantly, usng locaton nformaton as a pror knowledge, geometry technques (e.g., spanner sub graphs and Eucldean mnmum spannng trees) can be appled to topology control [26]. Coverage: Coverage reflects how well a sensor network observes the physcal space; thus, t can be vewed as the qualty of servce (QoS) of the sensng functon. Coverage desgns fall nto two categores. The probablstc approaches [28, 29, 30] analyze the node densty for ensurng approprate coverage statstcally, but essentally have no guarantee on the result. In contrast, the geometrc approaches [31] are able to obtan accurate and relable results, n whch locatons are essental.

40 18 Boundary detecton: Boundary detecton s to fgure out the overall boundary of an area montored by a WSN. There are two knds of boundares: the outer boundary showng the undersensed area, and the nner boundary ndcatng holes n a network deployment. The knowledge of boundary facltates the desgn of routng, load balancng, and network management [32]. As drect evdence, locaton nformaton helps to dentfy border nodes and further depct the network boundary. Clusterng: To facltate network management, researchers often propose to group sensor nodes nto clusters and organze nodes herarchcally [33]. In general, the ordnary nodes talk to other nodes wthn the same cluster, and the nter-cluster communcatons rely on a specal node n each cluster, whch s often called as cluster head. Cluster heads form a backbone of a network, based on whch the network-wde connectvty s mantaned. Clusterng brngs numerous advantages on network operatons, such as mprovng network scalablty, localzng the nformaton exchange, stablzng the network topology, and ncreasng network lfe tme. Among all possble solutons, locaton-based clusterng approaches are greatly effcent by generatng non-overlapped clusters. In addton, locaton nformaton can also be used to rebuld clusters locally when new nodes jon the network or some nodes suffer from hardware falure [33] Localzaton challenges and desgn ssues It s possble for a node to have up-to-date nformaton on ts locaton f t contans locaton determnaton hardware, such as a GPS recever, mounted on t. Unfortunately, for large number of sensor nodes, straghtforward soluton of addng GPS to all nodes n the network s not feasble because: Dense forests and mountans or other obstacles block the lne-of-sght sgnal from GPS satelltes and hence GPS cannot be mplemented. The power consumpton of GPS wll reduce the battery lfe of the sensor nodes and also reduce the effectve lfetme of the entre network.

41 19 In a network wth large number of nodes, the producton cost factor of GPS s an mportant ssue. The sze of GPS and ts antenna crcutry ncreases the sensor nodes form factor. Above factors llustrate that, from an economc standpont, t may not be feasble for all the nodes to be equpped wth specal hardware GPS. Hence, an alternate soluton s to equp a small fracton of the nodes n the network wth such hardware. Such nodes, called anchor nodes or beacon nodes, can act as reference ponts for locaton nformaton and the other sensor nodes, called as target nodes or non-anchor nodes or unknown nodes, can use nformaton from anchor nodes to estmate ther locaton Localzaton algorthm objectves The prmary objectves, to consder for the desgn of localzaton algorthms, are [34]: The localzaton algorthm must estmate poston: One of the man objectves of localzaton algorthms s to compute accurate estmates of sensors postons. The process of determnng node locaton from anchor ponts can be summarzed n three general steps. For each node, ) Estmate the dstance to several anchor nodes and store anchor coordnates. ) Calculate node poston from anchor dstance estmates and anchor coordnates. ) Refne the node poston estmate usng addtonal nformaton (.e., more anchor measurements, addtonal sensor readngs, etc.). The localzaton algorthm must be accurate: Nodes must know ther poston wth an accuracy of one or two centmeters. The localzaton algorthm must be adhoc: Asde from computng node correspondence ponts, the network must establsh a global coordnate system entrely on ts own. The localzaton algorthm must have low overhead: Localzaton and tme synchronzaton must be acheved wthout sgnfcantly mpactng communcaton bandwdth that mght be

42 20 needed for other sensor network tasks. For smlar reasons, processor utlzaton must also be mnmal. The localzaton algorthm must be robust: It should be relatvely unaffected by node falure and range error [35] Classfcaton of localzaton algorthms The localzaton algorthm s the man component of a localzaton system. It estmates the locatons of sensors by usng knowledge of the absolute postons of few anchor nodes and nter-sensor measurements such as dstance and bearng measurements whch has been estmated usng any of dstance measurement technques. Localzaton algorthms can be classfed nto three categores: 1. Anchor-based v/s Anchor-free 2.Centralzed v/s Dstrbuted 3. Mobleanchor or Moble-beacon based.. Anchor-based v/s Anchor-free Anchor-based localzaton schemes requre few anchor or reference nodes whch already know ther absolute locatons va GPS or manual confguraton. The densty of the anchors depends on the characterstcs and probably the budget of the network snce GPS s a costly soluton. Anchors are typcally equpped wth hgh power transmtters to broadcast ther locaton nformaton called beacon sgnals/messages. Based on ths, other sensor nodes can compute ther own locatons usng the knowledge of the known locatons and the communcaton lnks. Anchor-based localzaton schemes can be further dvded nto range-based and range-free localzaton schemes. Range-based schemes nvolve nodes determnng ther dstance from beacons whch know ther postons, whereas n the range-free case, the only nformaton that s avalable s the exstence of the beacons n the neghborhood of the node. Range-based localzaton schemes use absolute pont-to-pont dstance or angle nformaton to calculate the locaton between neghborng sensors. Common technques for dstance angle estmaton nclude Tme of Arrval (TOA), Tme Dfference of Arrval (TDOA), Angle of Arrval (AOA), and Receved Sgnal Strength (RSS). Range-based protocols reman cost-neffectve due to the cost

43 21 of hardware for rado, sound, or vdeo sgnals, as well as the strct requrements on tme synchronzaton and energy consumpton. Range-free localzaton schemes are beng pursued as a cost-effectve alternatve to more expensve range-based approaches. In the range-free localzaton schemes, nodes determne ther locaton wthout any tme, angle, or power measurements. In contrast to the anchor-based localzaton schemes, anchor-free localzaton schemes crcumvent the dsadvantages by removng the beacons. Beacon-less locaton dscovery overcome the sngle pont falure at the beacon nodes. Sensor nodes do not need assstance from other postonng systems, lke GPS. However, n the case of anchor-free schemes the deployment has a drect nfluence on the accuracy of localzaton. An accurate modelng of deployment knowledge s therefore requred.. Centralzed v/s Dstrbuted Centralzed algorthms are desgned to run on a central machne wth suffcent computatonal power. Each sensor node gathers the measurements of dstances to all ts neghbors and passes them to the central staton where the postons of nodes are calculated. The computed postons are transmtted back to the nodes n the network. Centralzed algorthms overcome the problem of nodes computatonal lmtatons by acceptng the communcaton cost of movng data back to the central staton. Ths trade-off becomes less effectve as the network grows larger, because t unduly stresses nodes near the base staton. Furthermore, the data transmsson to the central staton nvolves tme delays, so the centralzed technques cannot be acceptable n many applcatons (e.g., moble nodes). In contrast, dstrbuted algorthms are desgned to run n the network where computaton takes place at every node. Each node s responsble for determnng ts poston usng neghborng nformaton. It offers a sgnfcant reducton n computaton requrements because the number of neghbors s usually not large (between ten and twenty), so the number of connectons s usually a few orders of magntude less. The use of a dstrbuted computaton

44 22 model s also tolerant to node falures and dstrbutes the communcaton cost evenly across the sensor nodes. On the other hand, dstrbuted algorthms mplementaton s often connected wth the loss of nformaton and because of that the results whch can be obtaned are usually less accurate. Dstrbuted localzaton can be classfed nto three classes: Beacon-based dstrbuted algorthms: Beacon-based dstrbuted algorthms start wth some group of beacons and nodes n the network to obtan a dstance measurement to a few beacons, and then use these measurements to determne ther own locaton. Relaxaton-based dstrbuted algorthms: Relaxaton-based dstrbuted algorthms use a coarse algorthm to roughly localze nodes n the network. Ths coarse algorthm s followed by a refnement step, whch typcally nvolves each node adjustng ts poston to approxmate the optmal soluton. Coordnate system sttchng based dstrbuted algorthms: In Coordnate system sttchng the network s dvded nto small overlappng sub regons, each of whch creates an optmal local map. Next the scheme merges the local maps nto a sngle global map.. Moble anchor or beacon-based Beacon nodes are powerful but expensve, hence t s desrable to mnmze the number of beacons to be used to estmate the poston of each sensor node. Ths s acheved by movng a beacon around the area by perodcally broadcastng ts poston to nodes n ts vcnty. Such a poston-aware beacon can acqure ts geographcal poston through GPS, or the poston can be known, because t moves along a predefned route. Usng a movng beacon that knows ts poston s broadly equvalent to usng many statonary beacons, each broadcastng once. A sensor node can compute an area to confne ts locaton f t receves the beacon messages perodcally from the moble beacon. Once a sensor node has approxmately determned ts poston, t can help to localze ts neghbor nodes or even dstant nodes.

45 Organzaton of the thess The rest of the thess s organzed as follows: Chapter 2 presents lterature survey conducted over routng protocols and localzaton technques/algorthms used n WSNs. We dscuss some of the exstng routng protocols by groupng them nto three categores: load balancng, servce dfferentated and QoS based routng protocols. We also present the localzaton technques/algorthm by groupng them nto three categores: Anchor-based vs. Anchor-free, Centralzed vs. Dstrbuted and Moble-Anchor or Moble-Beacon based. Chapter 3 dscusses the research motvaton for development of routng protocols such as: Load Balancng Dynamc Adaptve Routng (LBDAR), Data Qualty Aware Routng (DQAR) and Energy-Buffer Aware Relable Routng (EBARR) and localzaton algorthm, namely Moble Anchor Asssted Localzaton (MAAL). Also, objectves of the proposed routng protocols and localzaton algorthm are presented. Chapter 4 presents the proposed LBDAR Protocol, whch mproves the network longevty by balancng energy consumpton across the nodes. At the outset, chapter provdes the models used, and desgn approaches for load balancng and defntons, whch s followed by the workng and performance analyss of the proposed protocol. Chapter 5 dscusses the proposed DQAR protocol. Ths protocol provdes dfferentated servces to ncrease the relablty of hgh prorty flows at each hop by ntroducng a new archtecture at ntermedate node, to balance node energy utlzaton and to ncrease the network lfetme. At the outset, chapter provdes mechansm for constructon of Angle Based Router Set whch helps to construct shortest multple paths by confnng paths towards the snk. Ths s followed by dscussons on the QoS provsonng mechansms, such as Dynamc multpath exploraton, Hop-by-hop uncastng wth request reply polcy, Energy Reservaton and Packet schedulng and servcng, employed by the DQAR to acheve servce dfferentaton for hgh prorty flows. Later we present the workng of proposed protocol. Analytcal model s presented to analyze average watng tme and servce tme for hgh prorty flows usng Prorty M/G/1

46 24 queue model. The performance of the DQAR s evaluated through smulaton and results are analyzed. Chapter 6 provdes the dscusson on the proposed EBARR whch meets both challenges of relablty and tmely delvery of crtcal data. We present the effcent QoS provsonng mechansms to acheve relablty and tmely delvery of crtcal data. The detals on handlng the buffer overflow to mtgate packet loss and acheve requred relablty s presented. A probablstc model s developed to evaluate packet losses due to buffer overflow and servce delay of hgh prorty flow at ntermedate nodes. The performance of EBARR s evaluated through smulaton and results are analyzed wth respect to dfferent combnaton of network and traffc control parameters. Chapter 7 presents a new MAAL algorthm. It s a range-based algorthm, n whch moble anchor node, equpped wth the GPS, moves n the sensng feld and broadcasts ts current poston perodcally. The sensor nodes obtanng the nformaton are able to compute ther locatons usng least square method. The detals of trajectory of moble anchor node, beacon nterval and dstance computaton usng RSSI are gven. The locaton computaton usng least square method s also presented. The MAAL s smulated and the results are presented on broadcastng nterval, rado range and movng speed of moble anchor. Chapter 8 provdes concluson. Appendx explans provdes the nference model used n our work. It also supplements detals on dstance computaton usng RSSI.

47 CHAPTER 2 ENERGY-EFFICIENT ROUTING PROTOCOLS AND LOCALIZATION ALGORITHMS: A LITERATURE SURVEY In ths chapter we dscuss some of the developed and mplemented energy effcent routng protocols and localzaton algorthms for WSNs. 2.1 Routng protocols The applcatons of WSNs comprses of wde varety of scenaros. Developng routng protocols for such scenaros demands the adopton of routng servce to the applcaton specfc requrements. Three routng servces dentfed are 1. Load balancng 2. Servce dfferentaton 3. Relable and tmely delvery. In ths secton we dscuss some of the routng protocols whch are developed and mplemented to address the above mentoned routng servces Energy-effcent Load balancng routng protocols Several routng protocols have been proposed n the recent decade that consders energy consumpton problem, and attemptng to balance the energy depleton and maxmzng the network lfetme. Based on the mechansm/approach used by the protocol to balance the load, we have categorzed the exstng protocols nto three groups, namely:. Classcal multpath. Cluster-based. Hop-by-hop resource aware

48 26. Classcal multpath Mult-path routng represents a promsng routng method to dstrbute the load n WSNs. Classcal multpath routng has been explored for two reasons. The frst s load balancng: traffc between a source-destnaton par s splt across multple (partally or completely) dsjont paths. The second use of multpath routng s to ncrease the lkelhood of relable data delvery. Some of the exstng load balancng routng protocols whch employ classcal multpath routng scheme to balance energy consumpton are dscussed n the followng paragraphs. Shah.et.al.,[36], propose a protocol that employs multpath routng to dstrbute energy load across the network. In ths protocol multple paths are found between source and destnaton, and each path s assgned a probablty of beng chosen, dependng on the energy metrc. Every tme data s to be sent from source to destnaton, one of the paths s randomly chosen dependng on the probabltes. Ths means that none of the paths are used all the tme, preventng energy depleton. The multpath routng mechansms allow the establshment of multple paths between source and destnaton. Energy Balancng Multpath Routng (EBMR) [37] s dfferent from the proposed multpath routng protocols [38], n the methods of establshng, selectng and mantanng routng paths. It ncreases the lfetme of the sensor network and reduces the addtonal route mantenance overhead due to the dfferent way the route path beng selected. The basc dea of EBMR s that nstead of usng source-ntated or destnaton-ntated route dscovery, t s the base staton that fnds multpath to the source of the data and selects one to use durng the communcaton. Furthermore, the base staton dynamcally updates the avalable energy of each node along the path based on the amount of packets beng sent and receved. The base staton then uses the updated energy condton to perodcally select a new path from multpath. An energy-effcent multpath routng algorthm s proposed n [39]. The man dea of the protocol s to dstrbute the traffc load. To acheve ths, the protocol dscovers multple nodedsjont paths between the snk and source nodes. It dstrbutes the traffc over the dscovered multple paths. The protocol allows the snk node to allocate the traffc over multple paths found

49 27 based on ther cost, whch depends on the energy levels and the hop dstances of nodes along each path. The multpath routng scheme n [39] pro-actvely constructs and mantans a small number of alternate (partally) dsjont routng paths and uses them whenever the prmary path fals. Although ths restrcts the network-wde floodng to dscover an alternate path, t ncurs a hgh overhead n dscoverng and mantanng multple paths. An energy-aware load balanced routng scheme s proposed n [40] whch proactvely fnds multple shortest routng paths. Based on the remanng energy level n the next hop sensors on the paths, t chooses one of the multple paths when message forwardng takes place. Ths scheme may lead to sensors consumng extra energy due to contnuously montorng and collectng the remanng energy level from the neghborng nodes. In [41], a route load balancng scheme s proposed based on a constraned random walk on a cubc grd topology. Ths scheme forces two constrants: 1. neghbors wth a shorter dstance to the destnaton are selected, and 2. those neghbors are equally lkely to be selected to dstrbute the ncomng traffc load. However, due to the dstancebased neghbor selecton and the unform traffc dstrbuton, the proposed scheme does not offer any flexblty to control the amount of data traffc load for each sensor nor the data delvery latency n a random topology. In [42], a new energy effcent packet forwardng scheme has been proposed to ncrease the survvablty of low-energy networks. The man dea s to balance the energy consumpton among the sensor nodes to avod early depleton of the networks. Usng a determnstc crtera, ths protocol selects the paths that have the hgher relaton of nodes energy reserves and dstance to destnaton. A new On balancng energy consumpton protocol s proposed n [43], whch balances energy consumpton by sendng the traffc generated by each sensor node through multple paths, nstead of a sngle path. It mnmzes the total amount of energy consumed by the network n forwardng a packet between any par of nodes. In order to utlze energy effcently and maxmze the network lfetme protocol uses load balancng schemes.

50 28. Cluster-based approach The conventonal protocols of drect transmsson, mnmum-transmsson-energy routng and statc clusterng may not be optmal for sensor networks and, hence LEACH[44] (Low- Energy Adaptve Clusterng Herarchy), a clusterng-based protocol that utlzes randomzed rotaton of local cluster base statons (cluster-heads) to evenly dstrbute the energy load among the sensors n the network. Ths routng mechansm saves energy snce the transmssons are manly managed by cluster heads. Intally cluster heads are randomly selected and changed over tme n order to spread load and balance the energy dspersons of nodes. A cluster head compresses data arrvng from nodes belongng to ts cluster and sends an aggregated packet to the snk. Adaptve clusterng s employed to ncrease the lfetme of the system. LEACH assumes that each node has enough power to transmt sgnals to reach cluster head and has equal computatonal power to work n dfferent MAC protocols. Thus t s not applcable to deploy n large regons due to the varaton of dstances between sensors and head of clusters [8]. Moreover the dea of dynamc clusterng brngs extra overhead, such as rotaton of cluster head, advertsement etc., and accordngly consumes energy. In TEEN [45], sensor nodes sense the medum contnuously, whle data transmsson s done at less frequency for savng energy. A cluster head sends ts members two thresholds namely, the hard threshold and soft threshold. The node wll transmt data only when the current value of the sensed attrbute s greater than the hard threshold. Adaptve threshold senstve Energy Effcent sensor Network protocol (APTEEN) [46] s an extenson of TEEN protocol. It can be used for both perodc and responsve data collecton. The dsadvantage of the two approaches s overhead and complexty of formng clusters. The snk s engaged n formng the clusters, whch obvously creates a lot of network traffc. Another drawback of the protocol s mantanng the threshold-based functons. The Energy-Aware On-Demand Routng [47] ncreases the lfetme of a network by routng around the nodes that are runnng low n battery. In addton, t turns off the rado nterfaces dynamcally durng the perods when the nodes are dle. In Power Aware Organzaton

51 29 protocol [48], the sensor nodes are dvded nto dsjonted sets coverng the area to be montored. In every set a sngle node can be actvated whle other nodes are set to a low-energy sleep state. The Perodc, Event-drven and Query-based (PEQ) routng protocol [49] was desgned to support low latency, relablty, fast path recovery and low energy consumpton smultaneously. The basc dea of the PEQ s to use ordnary motes and a smple algorthm that uses the hop level of the nodes as the man nformaton to mnmze data transmsson. Another protocol, energy-aware and context-aware routng of sensor data [50] calls for network clusterng and assgns a less-energy-constraned gateway node that acts as a centralzed network manager. Based on energy usage at every sensor node and changes n the msson and the envronment, the gateway sets routes for sensor data, montors latency throughout the cluster, and arbtrates medum access among sensors.. Hop-by-hop resource aware In ths scheme, routng protocol explots the multhop aspect of sensor network communcaton. Snce sensor networks are densely deployed, each node s havng a set of neghbor node n ts communcaton range. At each hop, each node autonomously decdes whch one of the neghbor node should be the next hop node based on ther energy status, hop dstance to destnaton etc. Ths type of router selecton mantans good energy health across the network. Some of the protocols whch employ ths mechansm are: In mnmum-hop Routng [51], an optmal path to the snk node s determned based on two metrcs such as hop count and energy level. The node wth mnmum hop count to the snk node s selected. When several nodes havng the same hop count exst, the sensor node wth the most energy should be chosen as the next recpent to relay data packet. In [52], a specal packet s flooded to establsh a local routng table for every node n the network before data transmsson. The routng table conssts of parent, sblng, and chld nodes, together wth ther dentfcaton numbers and energy levels, wthn one hop dstance. MAP may

52 30 choose a longer path that wll provde better dstrbuton of the energy consumpton among the sensor nodes. Drected Dffuson [2] s a dfferent communcaton paradgm specfcally for sensor networks to save energy. It s a destnaton ntated reactve protocol that s data-centrc and applcaton aware. Dffuson works well for sensor networks where queres lke Send me the temperature data n a partcular area and ther responses are the domnant form of communcaton. A destnaton node (controller) requests data by sendng nterests for data. Ths nterest s flooded over the network, but each node only knows the neghbor from whom t got the request, and t sets up a gradent to send data to the neghbor. So by ths process, the nterest reaches the source node (sensor), but each node only knows ts neghbor(s) who asked for the data, not the fnal consumer of the data. Snce t s concevable that each node would receve the same nterest from more than one neghbor, data would come down to the controller node along multple paths. Of these, one hgh rate path s defned and the rest of the paths reman low rate. Ths s acheved by sendng out postve renforcements to ncrease the rate of a partcular path. There s also a mechansm for negatve renforcements to change hgh rate paths to low rate ones; these are used when a better path emerges. Chang et al. [53] propose a flow redrecton algorthm whch balances the energy consumpton rates among the nodes n proporton to the energy avalable. The objectve of ths scheme s to maxmze the lfetme of the system nstead of mnmzng the consumed power. The routng protocol [54] aggregates packet streams n a robust way, resultng n energy reductons of a factor 2 to 3. And also more unform resource utlzaton s acheved by shapng the traffc flow. The PBMR [55] enables balanced power consumpton n a network by managng the routng reply tme. The route constructon mechansm consders energy usage, and, as a result, t attans balanced energy consumpton. Exstng transmsson polces, however, cause an extremely unbalanced energy usage that contrbutes to early demse of some sensors reducng overall network s lfetme drastcally. Three transmsson polces are proposed n [56] to extend network lfetme through mproved dstrbuton of energy usage among sensors.

53 Routng protocols for servce dfferentaton Sensor networks are meant for sensng and dssemnatng nformaton about the envronment they sense. The crtcalty of a sensed phenomenon determnes t s mportance to the end user. Hence data dssemnaton n a sensor network should be nformaton aware. Such nformaton-awareness s essental frstly to dssemnate crtcal nformaton more relably and secondly to consume network resources proportonal to crtcalty of nformaton. Also, t s necessary to develop routng protocols whch provde dfferentated servce to crtcal packets. There have been a few publshed work on such routng protocols. A bref revew of these protocols s gven below. The concept of such a dfferentated servces and data prortzng framework for sensor networks was ntroduced n [57]. A multpath-multpacket forwardng protocol was proposed for delverng data packets at requred relablty based on data prorty. By usng redundancy n packets the protocol controls the relablty of packet delvery. The protocol uses a probablstc floodng scheme to create multple paths form source to snk. It adapts to any channel error and topologcal changes. However the man drawback of the algorthm s that t requres perodc update of forwardng parameters to adapt to the changes and also t doesn t provde any guarantee that the hgh prorty flows wll satsfy ther delay constrants. On the other hand, QoS-aware routng approaches [58] use set of paths called crtcal paths that are used to route the crtcal traffc wth a delay less than or equal to that acceptable to the tme crtcal applcatons. The ncomng traffc s dfferentated as crtcal and non crtcal, usng a feld n the packet header. However, these protocols do not ensure that hgh prorty packets wll be transmtted successfully to the snk. In [59], k multple node-dsjont paths are constructed from source to destnaton [2,60,61] and traffc rate s allocated to each path optmally. These alternate paths are kept alve by sendng perodc messages. However, network relablty can be ncreased at the expense of ncreased overhead of mantanng the alternate paths.

54 32 A cluster based QoS aware routng protocol [62] that employs a queung model to handle both real-tme and non-real-tme traffc, only consders the end-to-end delay. The protocol assocates a cost functon wth each lnk and uses the K-least-cost path algorthm to fnd a set of the best canddate routes. Each of the routes s checked aganst the end-to-end constrants and the route that satsfes the constrants s chosen to send the data to the snk. Furthermore, the transmsson delay s not consdered n the estmaton of the end-to-end delay, whch sometmes results n selectng routes that do not meet the requred end-to-end delay. However, the problem of bandwdth assgnment s solved n [63] by assgnng a dfferent bandwdth rato for each type of traffc for each node. RAP [64] uses velocty monotonc schedulng (VMS) to assgn hgh prorty to real tme traffc and prortzes access to the wreless medum n a manner smlar to the prortzed access scheme. VMS s based on a noton of packet requested velocty. Each packet s expected to make ts end-to-end deadlne f t can move towards the destnaton at ts requested velocty, whch reflects ts local urgency. Compared wth non prortzed packet schedulng, VMS mproves the deadlne mss ratos of sensor networks by gvng hgher prorty to packets wth hgher requested veloctes. VMS can outperform deadlne-based packet schedulng because velocty more accurately reflects the local urgency at each hop when packets wth the same deadlne have dfferent dstances to ther destnatons. Assumng that each sensor knows ts own locaton (usng GPS or other locaton servces [65]), the requested velocty can be determned locally. Ths property enables VMS to scale well n large-scale sensor networks. Some end-to-end relablty ssues n WSNs are solved n [66,67]. ReInForM [66] provdes desred relablty n data delvery based on packet prorty. Data can be delvered at desred levels of relablty at proportonal cost, n spte of the presence of sgnfcant channel errors. It uses the concept of dynamc packet state n context of sensor networks to control the number of paths requred for the desred relablty usng only local knowledge of channel error rates and does not requre any pror computaton or mantenance of these multple paths. Reference [67] consders the need for nformaton-awareness and adaptablty to channel errors along wth dfferentated allocaton of network resources based on the crtcalty of data.

55 33 Based on the crtcalty of the data nsde a packet, dfferent prorty levels are assgned, each prorty level maps to a desred relablty for data delvery. Three prorty ndex assgnment polces for mult-hop wreless networks are proposed n [68]. The Tme-To-Lve (TTL) polcy assgns prorty to a packet based on ts TTL counter, whle each node decreases TTL by the tme t spent n that node. The TTL-based prorty can dynamcally adapt packet prortes based on ts progress Routng protocols for relable and tmely delvery There are some crtcal applcatons whch demand QoS routng protocols. QoS routng s usually performed through resource reservaton n a connecton-orented communcaton n order to meet the requrements for each ndvdual connecton. The problems of relable transmsson and tmely delvery of crtcal nformaton n WSNs have been the subject of ntensve research n recent years. Both sngle path and multpath routng are explored to provde energy effcent, relable and low latency servces. These protocols prmarly focus on load balancng, fault tolerance, bandwdth aggregaton, and reduced delay. Even though, these benefts are provded, the man problem assocated wth multpath routng s route couplng. In [69], the problem of route couplng has been studed and a measure s proposed for the couplng between two routes usng a correlaton factor. An N-to-1 multpath dscovery protocol s proposed n [70] whch fnds dfferent node-dsjont paths between a snk and a source node. These alternatve routes are used to dstrbute traffc n order to mprove the relablty and the securty of the data transmsson. Recently few research projects have started to address the support of QoS requrements n wreless sensor networks. Some QoS orented routng proposals are surveyed n [71,72]. In ths secton, we present the state of the research summarzng the publshed work and hghlghtng the QoS ssues beng addressed, we also observe that the exstng work fall nto two categores : tradtonal end-to-end QoS and applcaton-specfc. A bref revew s provded n the followng dscussons.

56 34. Tradtonal end-to-end QoS One of the early proposed routng protocols that provde QoS s the Sequental Assgnment Routng (SAR) protocol [73]. SAR protocol s a mult-path routng protocol that makes routng decsons based on three factors: energy resources, QoS on each path, and packet's prorty levels. Multple paths are created by buldng a tree rooted at the source to the destnaton. Durng constructon of paths those nodes whch have low QoS and low resdual energy are avoded. Upon the constructon of the tree, most of the nodes wll belong to multple paths. To transmt data to snk, SAR computes a weghted QoS metrc as a product of the addtve QoS metrc and a weghted coeffcent assocated wth the prorty level of the packet to select a path. Employng multple paths ncreases fault tolerance, but SAR protocol suffers from the overhead of mantanng routng tables and QoS metrcs at each sensor node. SPEED [74] s another QoS based routng protocol that provdes soft real-tme end-toend guarantees. Each sensor node mantans nformaton about ts neghbors and explots geographc forwardng to fnd the paths. To ensure packet delvery wthn the requred tme lmts, SPEED enables the applcaton to compute the end-to-end delay by dvdng the dstance to the snk by the speed of packet delvery before makng any admsson decson. Furthermore, SPEED can provde congeston avodance when the network s congested. However, smulaton results [18] have shown that SPEED outperforms other protocols, ths does not mean that SPEED s an energy effcent protocol because the protocols used n the head to head comparson are not energy aware protocols. The SPEED protocol does not consder any energy metrc n ts routng protocol, whch makes a queston about ts energy effcency. Message-ntated Constraned-Based Routng (MCBR) mechansm s proposed n [75]. MCBR s composed of explct specfcatons of constrant-based destnatons, route constrants and QoS requrements for messages, and a set of QoS aware meta-strateges. Gven the destnaton and routng constrants, routes from the source to the destnaton are establshed through floodng the network. Through applyng general purpose meta routng strateges, a data message s routed from source to destnaton va a route that satsfes the QoS requrements for that data message. However, the extra control packets (because of floodng the network wth

57 35 control packets) are a sgnfcant overhead. Same authors have proposed the QoS aware learnng based routng to decrease the complexty of MCBR protocol and enhance ts performance [76]. MMSPEED (Mult-path and Mult-SPEED routng protocol) proposed n [77] s one of the frst protocols to provde dfferentaton n two QoS domans: tmelness and relablty. Multple QoS levels are provded n the tmelnes doman by usng dfferent delvery speeds. The method used by the MMSPEED to obtan relablty s the typcal multpath forwardng scheme, wth a number of paths that depend on the requred degree of relablty for the traffc flows. However, MMSPEED lacks a method for dealng wth the data redundancy problem, whch resulted n consumng a large amount of energy [78]. A mult constraned QoS mult-path routng (MCMP) protocol [79] uses braded routes to delver packets to the snk node accordng to certan QoS requrements expressed n terms of relablty and delay. The problem of end-to-end delay s formulated as an optmzaton problem whch s a probablstc programmng, and then an algorthm based on lnear nteger programmng s appled to solve the problem. Algorthm checks the feasblty of lnks wth delay constrant and relablty as routng parameter decsons. Local lnk metrcs and dstance to the snk n terms of hop count are used to estmate the path metrc. The current E2E QoS requrements are unformly parttoned at all downstream and hop requrement s computed. The end-to-end QoS requrement s obtaned by achevng hop requrement at each hop. A node can satsfy the hop requrement by selectng next hop nodes based on lnk condtons. Multple paths are used as a group to acheve the QoS requrement such as relablty. In order to dstrbute the relablty requrement among those paths, nodes have to determne the relablty dstrbuton on downstream lnks based on ther knowledge. By keepng the relablty dstrbuton on all successor nodes on paths to the snk, the expected relablty s acheved wth certan probablty. To mantan the relablty assgned by the precedng node, all next hop nodes adaptvely adjust the relablty dstrbuton among ther successors. The protocol s objectve s to utlze the multple paths to augment network performance wth moderate energy cost. However, the protocol always routes the nformaton over the path that ncludes mnmum number of hops to satsfy the requred QoS, whch leads to more energy

58 36 consumpton n some cases. And also, ths approach consders nether resdual energy nor progress speed whle routng the packet to the next node. Packets are duplcated at each hop and routed to a node whch s hghly congested and /or energy crtcal. In [80] a general relablty-centrc framework for event reportng s proposed. Ths protocol adopts smart prorty schedulng that dfferentates an event data of non-unform mportance to acheve desrable relablty wth mnmzed delay. QoS n relablty doman can be acheved by managng the strngent resource buffer. To the best of our knowledge only two types of buffer management polces are avalable for sensor network scenaro [81,82]. In [81], whle authors propose coverage aware buffer management polcy whch cannot ensure that loss rate s bounded packet for dfferent categores of packets and n [82], authors do not present any algorthm for complete lossless crtcal packets. Energy constraned mult-path routng (ECMP) protocol [83] extends the MCMP protocol by formulatng the QoS routng problem as an energy optmzaton problem constraned by relablty, play-back delay, and geo-spatal path selecton constrants. The ECMP protocol trades between mnmum number of hops and mnmum energy by selectng the path that satsfes the QoS requrements and mnmzes energy consumpton. QoS-based energy-effcent sensor routng (QuESt) protocol [84] determnes applcatonspecfc, near-optmal sensory-routes by optmzng multple QoS parameters (end-to-end delay and bandwdth requrements) and energy consumpton, based on the mult-objectve genetc algorthm (MOGA). The QuESt s capable of dscoverng a set of QoS based, near optmal routes even wth mprecse network nformaton. One of the recently proposed QoS based routng protocol, specfcally for wreless sensor networks, s an energy effcent and QoS aware multpath based routng (EQSR) [85], that provdes servce dfferentaton by gvng real-tme traffc absolute preferental treatment over the non-real-tme traffc. EQSR uses the mult-path paradgm together wth a Forward Error Correcton (FEC) technque to recover from node falures wthout nvokng network-wde floodng for path-dscovery. EQSR protocol uses the resdual energy, node avalable buffer sze,

59 37 and sgnal-to-nose rato to predct the next hop through the paths constructon phase. EQSR splts up the transmtted message nto a number of segments of equal sze, adds correcton codes, and then transmts t over multple paths smultaneously to ncrease the probablty that an essental porton of the packet s receved at the destnaton wthout ncurrng excessve delay. EQSR protocol handles both real-tme and non real-tme traffc effcently, by employng a queung model that provdes servce dfferentaton. A new localzed QoS routng protocol for WSN s proposed n [86].The proposed protocol targets WSN s applcatons havng dfferent types of data traffc. It s based on dfferentatng QoS requrements accordng to the data type, whch enables to provde several and customzed QoS metrcs for each traffc category. Wth each packet, the protocol attempts to fulfll the requred data-related QoS metrc(s) whle consderng power effcency. It s modular and uses geographcal nformaton, whch elmnates the need for propagatng routng nformaton. For lnk qualty estmaton, the protocol employs dstrbuted, memory and computaton effcent mechansms. It uses a multsnk sngle-path approach to ncrease relablty. The proposed protocol can operate wth any medum access control (MAC) protocol, provded that t employs an acknowledgment (ACK) mechansm. In [87] novel routng servce called n-mddle recovery s proposed. The man objectve of n-mddle recovery s to fll the gap between the tradtonal per hop recovery and E2E recovery, offerng a better servce n a more effcent way. The basc dea s that packet-loss s recovered n a several-hop manner rather than the per hop or E2E ones. To acheve ths dea, an nstance of n-mddle recovery called prolferaton routng s desgned and mplemented.. Applcaton-specfc However, there are some crtcal applcatons whch demand QoS routng protocols. QoS routng s usually performed through resource reservaton n a connecton-orented communcaton n order to meet the requrements for each ndvdual connecton. There exsts many mechansms whch have been proposed for routng QoS constraned real-tme multmeda

60 38 data n wred networks [88-91], whch cannot be drectly appled to wreless sensor networks due to lmted resources, such as bandwdth and energy. QoS has been defned n terms of optmum number of sensors that should be sendng nformaton at any gven tme [92]. They utlze the base staton to communcate QoS nformaton to each of the sensors usng a broadcast channel and explot the mathematcal paradgm of the Gur Game to dynamcally adjust to the optmum number of sensors. M. Perllo et al. [93] provde applcaton of QoS through the jont optmzaton of sensor schedulng and data routng, whch can also extend the lfetme of a network. Actually, ther goal s to balance the applcaton relablty wth effcent energy consumpton. In other papers [94] and [95], QoS s also defned as coverage or exposure - the basc dea s how to cover the desred area of nterest or leave no sensng holes so that sensors can detect unexpected events as quckly as possble wth maxmum relablty. 2.2 Localzaton Algorthms The performance of WSNs s nfluenced by how accurately sensor nodes wthn the network are localzed. Sensor localzaton nformaton s used n the self organzaton and confguraton of networks n decdng where events take place, trackng movng targets [96-98], assstng traffc routng [99,100], and provdng the network geographc coverage [101]. Whenever well establshed systems such as the Global Postonng Systems (GPS) are not vable, localzng network nodes becomes qute a challenge. Several localzaton schemes are developed whch actvely and dversely support locaton based servces and applcatons. We dvde exstng localzaton schemes nto three categores: 1.Range-based 2.Range-free and 3.Moble beacon-asssted scheme. A bref revew of the protocols whch are developed under each category s dscussed n followng subsectons Range-based schemes Range-based schemes explot range (dstance or angle) nformaton for estmatng locatons. The range nformaton can be acqured by usng Tme of Arrval (TOA), Tme

61 39 Dfference of Arrval (TDOA), Angle of Arrval (AOA), and Receved Sgnal Strength Indcator (RSSI) technologes [ ]. Several mechansms have been proposed to localze a node s locaton based on range-based approaches such as AOA [107], TOA [108], TDOA [109], and RSSI [110]. Some schemes convert receved sgnal strength to dstance nformaton and use trangulaton to compute a node s locaton [111,112]. Bergamo and Mazzn descrbe a trangulaton mechansm for localzaton and explore effects due to fadng and sensor moblty [113]. Pryantha et al. utlze beacon advertsements for rangng to determne possble locatons [114]. If a node receves the advertsement, the node s locaton s regarded wthn the beacon s regon. Moreover, dstrbuted multlateraton methods were proposed for estmatng postons for conformng to ad hoc sensor networks [115,116]. Some approaches calculate comparatve angles between neghborng nodes for angulatons [117,118]. The range-based schemes typcally provde hgh accuracy, less than 5m [65] n locaton error, but they requre more hardware on sensor nodes. However, range-based methods have two sgnfcant drawbacks: they requre costly addtonal hardware support, and fadng and nose can cause dstance measurement errors [113] Range-free schemes Range-free approaches do not requre accurate dstance measurements, but localze the unknown node based on anchor proxmty (e.g., Centrod [119], APIT [120]), network connectvty nformaton (e.g., DV-hop [121], MDS-MAP [122], SDP [123]), or localzaton events detecton (e.g., Lghthouse [124], Spotlght [125]). Another work took adaptve beacon placement algorthm for mprovng the Centrod scheme [126]. The DV-Hop scheme can be enhanced wth RSSI technology for locaton refnement [127]. Recently, some RSS-asssted range-free approaches are proposed, such as RSSL [128], PI [129], RSD [130]. Instead of usng absolute RSS to estmate the dstance between two nodes wth ordnary hardware, by contrastng the measured RSS values from the moble beacon to a sensor node, RSSL and PI utlze the varance of RSS to estmate the unknown node poston.

62 Moble beacon-asssted schemes Moble localzaton [ ] usng movng beacons avod the problems of statc localzaton methods. Galstyan et al. [136] propose a dstrbuted onlne algorthm usng a movng beacon to localze statc sensor networks. Ths was extended to a general model usng an unknown target, n whch rado communcaton and sensng constrants mnmze the area n whch a node mght be located. Hu and Evans [133] propose the Monte Carlo Localzaton for sensor networks, n whch both nodes and beacons can be moble. The poston of a node was teratvely refned usng n-relatonshp or out-relatonshp nformaton among nodes and beacons as a flter. Nether method, however, sought to account for how the movement of the beacon mght nfluence the accurate estmate of the postons of sensor nodes. In fact, the movement pattern of the beacon drectly lnks to the accuracy and accomplshment of the localzaton task. Another localzaton mechansm usng a sngle moble beacon transmttng ts current locaton s descrbed n [137]. A sensor node recevng the beacon can recognze that t s n the area around the moble beacon. Combned wth the RSSI technque, possble locatons of the sensor node can be estmated. The accuracy can be advanced when the sensor node receves more beacons. In [138] ultrasound technology was used to estmate the dstance from a sensor to a moble object. Neghborng sensor nodes cooperate to evaluate the dstance between themselves by explotng common tangent concept. As long as the node-to-node dstances are avalable, the poston of a sensor node can be measured by range based schemes. In [139] a probablstc localzaton scheme wth a moble beacon s estmated. A range-free localzaton scheme usng moble anchor ponts s presented n[140]. Each anchor pont equpped wth the GPS moves n the sensng feld and broadcasts ts current poston perodcally. The sensor nodes obtanng the nformaton are able to compute ther locatons. Wth ths scheme, no extra hardware or data communcaton s needed for the sensor nodes. Moreover, obstacles n the sensng felds can be tolerated. A dstrbuted method to localze sensor nodes usng a movng beacon s proposed n [141].The method allows a sensor node to locally compute ts poston estmate by usng the

63 41 arrval and departure nformaton of the beacon. Beacon s havng three movement patterns: the Sparse-Straght-Lne (SSL) movement pattern, the Dense-Straght-Lne (DSL) movement pattern, and the random movement pattern. The basc dea of ths scheme s to narrow down the possble locaton of a node by usng the arrval and departure constrant areas derved from the movng beacon.

64 CHAPTER 3 MOTIVATION AND OBJECTIVE OF THE WORK The dssertaton work concentrates on research problems n the area of routng and localzaton n WSNs. Three dfferent routng protocols to address routng ssues and a new localzaton technque are proposed. Ths chapter dscusses the motvaton behnd the development of effcent routng protocols and localzaton technque wth ther objectves. 3.1 Wreless sensor networks applcatons and routng Routng protocols that can facltate applcaton specfc servce guarantee n WSNs can consttute one of the key desgn objectves of current WSN research. Developng such routng protocol demands adopton of routng servce to the applcaton-specfc requrements. Based on applcaton requrement, three dfferent ssues n routng have been dentfed 1. Load balancng 2. Servce dfferentaton and 3. Relable and tmely delvery Load balancng Balancng load n WSN survellance applcatons such as mltary, envronmental, traffc etc, s mportant, snce nodes wth heavy load can exhaust node resources such as bandwdth,

65 43 processng power, battery energy, and memory storage. Furthermore, f one of the heavly loaded nodes s congested, t can lead to packet loss and buffer overflow, resultng n longer end-to-end delay, leavng the network wth a wde dsparty n the energy level of the nodes, dsconnectng or parttonng the network and degradaton of network lfe. The survellance applcatons demand a load balancng routng protocol, snce networks are expected to operate over a longer perod of tme n an unattended and hostle envronment wth mnmal montorng. The protocol should ensure that connectvty n a network s mantaned as long as possble, and the energy status of the entre network should be of the same order. If nodes n the network consume energy more equtably, then the nodes n the center of the network contnue to provde connectvty for longer, and the tme to network partton ncreases. Ths leads to a more graceful degradaton of the network, and s the dea of survvablty of networks. Hence, survellance applcatons demands desgn and development of routng protocols whose objectve s to dynamcally dstrbute the load to multple sensors, so that t leads to maxmzng the network lfetme Servce dfferentaton WSN that s deployed to serve montorng applcatons such as ndustry, forest, health etc., generates heterogeneous traffc. Data generated n network may be dverse wth dfferent and dynamc prortes and t demands a dfferentated data delvery servce from network nfrastructure. For nstance, the nformaton of chemcal leak, n nuclear power statons, s more mportant than knowng everythng s fne and nformaton should reach the snk wth hgh relablty and low latency, so that system responds to the event quckly by performng correspondng actons. Smlarly, n forest montorng applcatons, the sensor data that contans an abnormal hgh temperature should be delvered to the base staton wth hgh relablty n lmted tme duraton, snce t can be a sgn of fre. On the other hand the temperature

66 44 nformaton that s n the range of normal temperature can be delvered to the base staton wth certan delay and percentage of loss. Above examples manfest that data generated n WSN are not be alke and some data may be more mportant than other and hence may have dfferent delvery requrements. To meet ths, t s necessary to desgn effcent routng mechansm whch ams at dscrmnatng and provdng servce to the packets accordng to ther prorty, nstead of usng conventonal frst-nfrst-out packet forwardng scheme Relable and tmely delvery In many of real-tme applcatons such as survellance, object trackng and envronmental montorng of WSNs delverng tme constraned data has strong requrements for QoS assurance n terms of relablty and tmely delvery. Tme-constraned crtcal data s delay senstve and t has to be delvered to base staton wth hgh relablty so that mmedate remedal and defensve actons can be taken, whereas, perodc data s delay tolerant and certan percentage of loss s tolerable on delvery. For example, volcanc montorng s hghly delay senstve applcaton, where sensor nodes are deployed to montor the sesmc actvtes and emsson levels of volcanc craters and data should be transmtted to the snk wth more relablty and prescrbed delay, n observance of any unusual actvty. The delay and relablty are the performance metrcs and usually referred to as QoS requrements of crtcal data. Therefore, power constraned sensor networks for real tme applcatons have demanded energy and QoS aware routng protocol to delver the crtcal data wth low latency and hgh relablty. 3.2 Proposed routng protocols and ther objectves To meet the above applcaton requrements and ther routng objectves such as, load balancng, servce dfferentaton and relable and tmely delvery servce, three energy effcent routng protocols are proposed :

67 45. Load Balancng Dynamc Adaptve Routng (LBDAR) protocol. Data Qualty Aware Routng (DQAR) protocol. Energy Buffer Aware Relable Routng (EBARR) protocol whose objectves are detaled below:. Load Balancng Dynamc Adaptve Routng (LBDAR) protocol The LBDAR s a reactve protocol whch tres to ensure the unform depleton of energy across the nodes, wth an objectve to ncrease the energy conservaton and prolong the lfetme of sensor nodes. Ths protocol elmnates bottleneck of heavly nvolved nodes along the optmal path by computng new path for every data ntaton. As compared to mnmum hop routng and energy aware routng, the results of the LBDAR protocol demonstrate more unform usage of nodes wth effcent use of battery power. The network lfetme s ncreased by reducng the overloadng of ntermedate nodes by effcently selectng them whle routng. Snce network lfetme s ncreased, the packet delvery rato s comparatvely hgh n the LBDAR.. Data Qualty Aware Routng (DQAR) protocol The DQAR protocol for servce dfferentaton s developed wth an objectve to prortze and provde relablty assurance to hgh prorty packets compared to low and medum prorty packets. The results demonstrate that protocol s more effcent n provdng dfferentated servce to hgh prorty data packets and acheve hgh data delvery rato compared to mult path routng (MR) and mnmum energy routng (MER). The DQAR also ncreases the network lfetme by ensurng unform energy depleton across the nodes and hence acheves load balancng. Result also shows that, DQAR reduces end-to-end transmsson delay of hgh prorty packets by dynamcally constructng shortest paths (Results shown n chapter 5).. Energy Buffer Aware Relable Routng (EBARR) protocol A novel QoS aware routng protocol,.e., EBARR, s proposed to provde QoS n tmelness and relablty domans for crtcal packets generated n tme crtcal applcaton. The

68 46 performance of EBARR s evaluated wth respect to dfferent combnaton of network and traffc control parameters and compared t wth Multconstraned QoS multpath routng(mcmp) protocol. The results demonstrate that EBARR outperforms the MCMP protocol n achevng the desred performance for dverse data accordng to the prorty specfed by the snk. The EBARR also dstrbutes the traffc load and thus acheves hgher node energy effcency whch ncreases network lfetme. Results also prove that the EBARR meets both the challenges of relablty and tmely delvery of crtcal data effcently(results shown n chapter 6). 3.3 Localzaton and accuracy The node localzaton problem has receved a tremendous attenton from the research communty, thus emphaszng that t s an mportant and challengng task. The objectve of localzaton algorthm s to mprove the localzaton accuracy and maxmzng the coverage wth low communcaton cost by reducng hardware cost. However, localzaton accuracy s characterzed by two mportant hardware problems:. Expensve hardware (GPS). Anchor nodes.. Expensve hardware Sensor nodes equpped wth Geographcal Postonng System (GPS) devces are aware of ther locatons at a precson level of few meters. However, nstallng GPS devces on a large number of sensor nodes s not only expensve but affects the form factor of these nodes. Moreover, GPS-based localzaton s not applcable n the ndoor envronments such as buldngs. Despte the recent avalablty of small, energy-effcent GPS system-on-chp solutons that brng GPS wthn the sze and cost constrants of a sensor network, commercal GPS yelds poston estmates wth error bounds of several meters.. Anchor nodes Snce GPS s expensve, sensor localzaton can be done alternatvely by deployng anchor nodes. These are a small subset of nodes n the network and are often heavy weght

69 47 nodes, equpped wth addtonal sensng hardware, such as a GPS recever [142], or wth addtonal processng capablty [143]. Once anchor nodes are establshed, the remanng nodes, whch are termed moble nodes, must determne ther poston relatve to the anchor nodes. However, the localzaton accuracy largely depends on a small number of anchor nodes. When some of these nodes fal to functon or when they are tampered by cheatng beacon nodes a sgnfcant number of sensors can be affected,.e., ther derved locatons can be much far away from ther actual locatons. The densty of anchor nodes also determnes the locaton accuracy, locaton estmaton error and budget of the sensor network Proposed localzaton algorthm and ts objectves To reduce hardware cost whch ncurs due to expensve GPS and more number of anchor nodes n a sensng feld, a new range based cost effectve localzaton technque, called Moble Anchor Asssted Localzaton [MAAL] s proposed. The objectve of the proposed technque s to localze sensor nodes n two dmensonal space and to mprove the localzaton accuracy. In ths technque, a sngle moble anchor (MA) node equpped wth GPS moves n the sensng feld and broadcasts ts current poston perodcally. Once an unknown node receves beacon messages, RSSI s appled to compute the dstance between node and MA node. The estmated dstance values, assst the localzaton of unknown nodes. Wth ths technque, no extra hardware or data communcaton s needed for the sensor nodes. Moreover, obstacles n the sensng felds can be tolerated.

70 CHAPTER 4 LOAD BALANCING DYNAMIC ADAPTIVE ROUTING PROTOCOL Ths chapter presents the proposed reactve routng protocol called Load Balancng Dynamc Adaptve Routng (LBDAR) to mprove network longevty by balancng energy consumpton across sensor nodes. Before dscussng the workng of the protocol, we present the relevant models such as network, energy and traffc model whch are consdered for the desgn of the protocol. The proposed protocol uses dynamc approach to fnd effcent data routng structure and t s ntended to evenly dstrbute the load. 4.1 Models used The network model consdered by the protocol and functonaltes of sensor node are dscussed n secton Energy consumpton s one of the most mportant performance metrcs for WSNs because t drectly relates to the operatonal lfetme of the network. Energy consumpton at a sensor node depends on the type of energy model used at the sensor node. Secton dscusses the type of energy model used by the proposed protocol. The type of traffc ntated n WSN s dependent on applcaton and t s dscussed n secton

71 Network model Fgure 4.1 llustrates a WSN consstng of N number of sensor nodes deployed n a square sensng feld of area A wth sngle base staton or snk v * at the center. The network conssts of large number of sensor nodes, and these nodes sense and store the data. Whenever user needs any sensed data, base staton v * floods the user s request nto the network. Sensor nodes whch dentfy the request becomes Source Nodes (SNs) and begn to transmt sensed data towards the snk v *. Sensor nodes, whch help to forward sensed data from source to snk, are called Intermedate Nodes (INs). Sensor Nodes v * Snk Node Fgure 4.1: A typcal wreless sensor network model We make the followng assumptons for the network: All nodes are statonary, havng rado range r and are aware of ther own locaton usng any postonng or localzaton algorthm [ ]. The sensor nodes are left unattended after deployment. Therefore, energy cannot be recharged. The sensor nodes are homogeneous whch means that they have smlar processng and communcaton capablty.

72 50 Two sensor nodes are assumed to be neghbors f the Eucldean dstance between them s less than ther transmsson range r. The communcaton lnks are symmetrc. Thus, f node v can receve a packet from node u, node u can also receve that packet from node v. There are no bg obstacles between source node and snk node Energy Model Each sensor node has very lmted energy, for example, the total energy stored nsde the smart dust mote s 1 Joule [151]. Energy effcency s one of the prmary challengng ssues to the successful applcaton of WSNs because the tny sensors wth lmted energy cannot be recharged easly once they are deployed. Snce the rado devce s the man source of energy consumpton, desgnng an energy effcent routng algorthm for communcaton process s one of the key ssues for WSNs. There are some other sources of energy consumpton by the sensor nodes. For example, the technque of modulaton/demodulaton and codng/decodng from PHY layer consume certan amount of energy. In the MAC layer, more energy wll be wasted f states lke actve/dle/sleepng are not well scheduled. Other factors such as packet collson and overhearng wll waste the lmted energy resource [ ]. From the above dscusson, energy consumpton n a sensor node can also be classfed as useful energy consumpton and wasteful energy consumpton. The useful energy consumpton conssts of 1) transmttng/recevng data 2) processng query requests and 3) forwardng queres/data. The wasteful energy consumpton conssts of 1) dle lstenng to the meda 2) retransmttng due to packet collson 3) overhearng and 4) generatng/handlng control packets [155]. In general, the source of energy consumpton conssts of three parts, namely sensng, processng and communcaton. Here we consder the energy consumpton durng

73 51 communcaton process due to the fact that to transmt one bt of message over 100 meters consumes around 1000 tmes more energy than to process the message. There are many dfferent energy consumpton models used n WSNs. The energy consumpton model we use n ths thess s called the frst order rado model [156,157]. In ths model rado dsspates Eelec 50 nj/bt to run the transmtter or recever crcutry and amp 100 pj/bt/m 2 for the transmtter amplfer. Each sensor node wll consume the followng amount of energy: (symbols are shown under Lst of symbols on page xv) 1. Amount of energy to transmt a k -bt message over dstance d : E E Tx ( k, d) ETx _ elec ( k) ETx _ amp ( k, d) 2 Tx ( k, d) Eelec k amp k d (4.1) 2. Amount of energy to receve the data message: E Rx E ( k) E _ ( k) Rx elec ( k E k (4.2) Rx ) elec 3. Amount of energy to forward the data message: Etot ( k, d) ETx ( k, d) ERx( k) (4.3) Traffc Model There are four types of traffc patterns for WSNs [8, 72,158], namely: tme-based, eventdrven, query-based and hybrd traffc pattern. 1. Tme-based: In applcatons lke temperature and sesmc montorng, vdeo survellance systems etc., the commonly used traffc pattern s tme-based, where the response latency s not very mportant but a trend (lke a mean value) needs to be deduced or predcted based on long term observaton data. 2. Event-drven: Event-drven traffc pattern s used for applcatons lke target trackng or ntruson detecton etc. When a target s enterng nto the nearby regon of a sensor node, the

74 52 target wll be detected and tracked wth an ncreased (or burst) traffc sent by nvolved sensor nodes to remote snk node. 3. Query- based : In query-based routng protocol, once the remote snk node or the base staton requests certan types of nformaton from some area, t wll send a query lke send me the fourlegged anmal (or the hghest temperature) nformaton n the area of [x1, x2, y1, y2]. The query s attrbute-based and t can be sent through multcast or broadcast. Once the correspondng sensor nodes receve ths query, they wll send back ther data nformaton as a response to ths query wthn short tme. DD (Drected dffuson) [2,159] s a representatve of query-based routng protocol. 4. Hybrd traffc: Hybrd traffc pattern s also commonly used traffc model. For example, durng the tme-based traffc montorng perod, the remote snk node may send a query to demand for certan nformaton smultaneously. In ths chapter, an energy effcent LBDAR protocol s dscussed whch manly adopts query-based traffc model. 4.2 Desgn approaches for load balancng Effcent selecton of next hop node In order to mnmze the energy consumpton durng transmsson, routng protocols select few nodes and contnuously relay the traffc over these nodes. Ths leads to creaton of routng holes n the network as shown n Fgure 4.2, where routng hole s an anomaly caused due to vods n sensor deployment or falure of sensor nodes for varous reasons lke malfunctonng, battery depleton or an external event such as fre or physcal destructon of nodes. Because of these holes, neghborhood nodes may become naccessble, whch n turn leads to network parttonng. As a result, network lfetme and performance of the network decreases and hence, routng protocols have mpact on network lfetme whch defnes the network survvablty and connectvty. Therefore, t s mperatve to develop routng protocol

75 53 whch burns the energy among nodes more evenly so that the energy health of entre network should be of the same order. By dong so, the nodes n the centre of network contnue to provde connectvty for longer duraton and the tme to network partton ncreases. In order to reduce energy dsparty among nodes n the network, routng protocol must provde a good chance to all routers to actvely partcpate n forwardng data messages, nstead of selectng few nodes repeatedly. Holes Brake n transmsson Montorng regon Snk node Network parttonng Source nodes Intermedate nodes Fgure 4.2: An llustraton of creaton of holes n WSN To spread the routng load and mnmze dsparty n energy levels among nodes, a new routng decson s proposed at each hop. Ths routng decson s local to nodes and prevents repeated selecton of same node as next node, so that energy s depleted more evenly across the nodes and network contnues to provde connectvty Dynamc path exploraton To extend WSN lfetme, many routng protocols have been proposed wth energy awareness beng an essental desgn consderaton. These protocols fnd optmal paths and then burn the energy of the nodes along those paths, leavng the network wth a wde dsparty n the energy level of the nodes and fnally results n network partton. To counteract ths problem, proposed routng protocol dynamcally fnds the path from source to destnaton for every new

76 54 data ntaton at source node and s shown n Fgure 4.3. If data s forwarded n ths manner, energy s burnt more equtably across nodes n the network, and nodes n the center of the network contnue to provde connectvty for longer tme. Moreover, tme to network partton ncreases whch n turn leads to a more graceful degradaton of the network Adaptable threshold energy settng and montorng Whle routng data over dynamcally establshed paths, multhop routes can overlap and few nodes may serve as routers for varous multple routes orgnatng from varous source nodes as depcted n Fgure 4.3. As a result, energy at the shared node drans out sooner and leads to creaton of holes n the network. SN 1 SN 2 Shared router creatng holes SN 3 Path explored from source to destnaton at tme t 1 ` Path explored from source to destnaton at tme t 2 Path explored from source to destnaton at tme t 3 Fgure 4.3: Illustraton of dynamc path exploraton for every new data ntaton at source nodes We propose a new method to prevent shared nodes from beng selected and provde opportunty for other nodes to partcpate n data forwardng actvty. In ths method, threshold energy E thsh s mantaned at each node and t defnes level of energy exhauston that can be reached at a node. Once energy depleton level reaches E thsh, node enters nto dle state and sends

77 55 beacon sgnal to ts neghbors ndcatng threshold has been reached. E thsh s updated perodcally by settng mnmum energy E mn at each node. E mn s the energy that can be utlzed at each node for further transmssons. E thsh s computed wth the help of E mn as where E thsh Ecurrent E mn (4.4) Ecurrent s the currently avalable energy at the node. E thsh determnes elgblty of a sensor node for partcpatng n routng data. are E For example, f current avalable energy and mnmum energy defned at a node current exhausted and = 5j and E mn =1j, that node can be selected as a next hop node untl 1j s completely E thsh becomes 5j-1j = 4j. Once energy level drops to 4j, node enters nto reduced actvty and sends beacon sgnal to ts neghborng nodes ndcatng that threshold has been reached. Ths prevents from selectng the same node as a next hop node, creatng opportunty for other nodes to partcpate n further transmssons. Once all the nodes enter nto reduced actvty, a new threshold s set at each node by broadcastng new E mn value. As soon as new E mn s ntalzed, nodes enter nto actve mode and partcpate n forwardng the data message untl the new E mn value s exhausted. From the above dscusson, t s clear that threshold settng at a node prevents. node from beng repeatedly selected as a next router,. node from early depleton of ts energy, and. creaton of holes n the network at early stages, so that energy health across the network s mproved. Above all, ths type of threshold settng across nodes makes the LBDAR more effectve and adaptable to changes n the local nformaton of sensor nodes. 4.3 Defntons In ths secton we dscuss dfferent types of packets, defntons and tables used n the proposed protocol.

78 56 Interest Message Packet (IMP) IMP holds the user s query whch s n the form of attrbute-value par [2]. Fgure 4.4 shows the format of IMP. The feld Message type ndcates a request message and the feld task descrpton descrbes sensng task. For example, the anmal trackng task s descrbed as follows: Type = four-legged anmal // detect anmal locaton Interval = 20 ms // send back events every 20 ms Duraton = 10 seconds // for the next 10 seconds rect = [-100, 100, 200, 400] // from sensors wthn rectangle Message type Task descrpton Fgure 4.4: Format of IMP Frequency Count (FC) FC gves the number of tmes a node s beng chosen as a next hop n past communcaton actvtes. The count ncreases by one as t forwards data. Node Informaton Packet (NIP) Each node encapsulates ts node_d, frequency count and current_energy level n a packet called Node Informaton Packet whch s gven n Fgure 4.5. Node_d Current_energy Frequency Count (FC) Fgure 4.5: Format of NIP Interest Request Packet (IRP) Whenever a resource rch base staton v * needs any sensory data, t floods the request packet called Interest Request Packet throughout the network. IRP comprses of IMP and

79 57 NIP as shown n Fgure 4.6. When the packet s at base staton, the feld Node_ d takes the address of snk, the feld FC and current_energy level take value -1 and, respectvely. IMP NIP Fgure 4.6: Format of IRP Interest Cache Table (ICT) Each node mantans user s request n the form of task descrpton, n a table called nterest cache table whose format s shown n Fgure 4.7.The feld Sender_d lst n ICT gves the address of neghborng nodes from whch the request has been arrved. The feld Tme of arrval ndcates tme at whch user s request has arrved. Message type Task descrpton Tme of arrval Sender_d Lst Interest message request type 1 Eg: Temperature montorng task Interest message request type 2 Eg. Anmal trackng task Interval= 10ms Duraton= 20sec 0 Temperature = 45 type = four-legged anmal nterval = 20 ms duraton = 10sec rect = [-100, 100, 200, 400] 10hrs:20mns: 8sec IN 6,,IN 8,,IN 10 13hrs:40mn:12sec IN 3,,IN 2, Neghbor lst (NL) Fgure 4.7: Format of ICT Each sensor node has complete nformaton about ts one hop downstream neghborng nodes such as Node_d, frequency count, status and current_energy level. Neghborng nodes nformaton s stored n a table called neghbor lst and s shown n Table 4.1. Table 4.1 Neghbor lst of sensor node Node_ d Current_energy (joules) FC status IN Actve IN Actve IN Reduced actvty

80 LBDAR protocol Overvew As soon as nodes are deployed n an area, where an event s to be montored, snk node dffuses mnmum energy E mn nto the network, whch s specfed by the admnstrator. Eventually, all sensor nodes compute the E thsh and mantan the same, tll they receve the new E mn. Whenever user needs any data, the resource rch base staton njects the user s request nto the network by broadcastng IRP packet to ts frst hop neghborng nodes. Upon recevng IRP, each node checks to see f task descrpton matches wth ts sensory data. If no matchng exsts, the node adds new nterest nto ICT by creatng new entry n ICT. For requests regardng the same nterest but from dstnct senders, the node extracts nformaton that exsts n NIP and stores n neghbor lst. Once IRP s processed, node resends the IRP to a subset of ts neghbor nodes. Ths process s carred out recursvely untl a node dentfes user s request. Once node dentfes the user s request, t becomes source node and starts sendng data towards the snk. Data wll be forwarded to snk by employng load balancng mechansms dscussed n secton 4.2 such as dynamc path exploraton, threshold montorng and effcent selecton of next hop node. To llustrate, a WSN n Fgure 4.1 s modeled as drected graph G = {V, E} shown n Fgure 4.8, where the node set V = {v*, IN 1, IN 2,, IN13, IN 14, IN 15 } and E s the edge set. There s a edge d, j) E ( from sensor node IN to sensor node IN j f a sngle hop transmsson from IN to IN j s possble. In Fgure 4.8, a value par (v 1, v 2 ) at each node represents resdual battery power n joules and ntal frequency count at tme t 1.Whenever user needs any nformaton, the resource rch base staton, v*, njects user s request n the form of IRP to ts frst hop neghbors such as IN 1, IN 2 and IN 3. Snce sensory data at IN 1, IN 2 and IN 3 do not match wth task descrpton, each node records nterest request nto ther ICT, the sender nformaton nto NL and broadcasts IRP request to ther neghborng nodes. Durng floodng of IRP n the network, nodes IN 14 and IN 15 dentfes user s request and become source nodes, SN 1 and SN 2, respectvely. To begn data transmsson, SN 1 uses ts NL to choose next hop node. SN 1 chooses

81 59 IN 10 as next hop node to forward data, snce ts frequency count s less and has more energy. Smlarly, IN 10 chooses IN 8 as next hop node among neghborng nodes IN 8 and IN 7 to forward the data. Ths process s repeated at each hop tll data reaches the snk. The path traversed by the data durng ts transmsson from source SN 1 to snk s SN. * 1 IN10 IN8 IN1 v Smlarly, data orgnated at SN 2 s forwarded to snk on hop-by-hop manner and the path traversed by the data s SN. * 2 IN12 IN6 IN4 IN3 v (4.1j, 3) IN 9 SN 2 IN 13 IN 15 SN 1 IN 14 (4.2j, 3) IN 10 IN 11 (4.6j, 4) (4.3j, 2) (4.6j, 3) IN 7 (4.8j, 2) (4.89j, 3) IN 8 IN 1 (4.4j, 2) (4.5j, 5) IN 2 IN 4 IN 3 v* (,-1) IN 12 (4.6j, 3) IN 6 (4.7j, 3) IN 5 (4.4j, 2) (4.9j, 3) Fgure 4.8: A Graph of sensor nodes llustratng IRP floodng and dynamc path exploraton Protocol descrpton The protocol has four phases.. Threshold settng As soon as sensor nodes are deployed, snk node dffuses mnmum energy E mn nto the network, whch s specfed by the admnstrator. Eventually, all sensor nodes compute the E thsh and mantan the same, tll t receves the new E mn value.

82 60. IRP floodng In ths phase, whenever base staton needs nformaton, IRP s dssemnated throughout the network, as llustrated n Fgure 4.8. Every node, upon recevng the IRP packet does the followng: 1. Records the task descrpton, f t s fresh, nto ICT by extractng nterest message from IMP. 2. Store the NIP n the neghbor lst. 3. When a node receves multple copes of same IRP from dfferent INs, t dscards IMP and extract only NIP and stores n the neghbors lst by creatng new entry. 4. Changes the sender Id of NIP to tself and rebroadcast the IRP packet along wth ts NIP to ts one hop neghbors. When an approprate node receves nterest, one or more sensors become sources and ntate a data transmsson. Algorthm 4.1 shows the processng of IRP packet at each sensor node. Algorthm 4.1: Processng of IRP packet at sensor node Step1. Begn Step2. Input: IRP packet, ICT, NL Step3. /* checks for a new IRP packet */ for all the entres of ICT begn for f ( IRP( IMP ( task descrpton)) = = ICT (task descrpton) ) goto step 5; /* task descrpton already exsts */ end for Step4. /* add task descrpton nto ICT by creatng a new entry */ ICT (task descrpton )= IRP( IMP ( task descrpton)) Step5. /*add sender nformaton nto NL */ NL (Node_ Id) = IRP( NIP(node_d)); NL(Current_energy)= IRP( NIP(current_energy)); NL(FC)= IRP( NIP(FC)); NL(status)= actve ; Step6. /* replace felds n NIP wth recpent node values*/ IRP( NIP( sender_d )) = sensor node(node_d); IRP( NIP (current_energy)) = sensor node(current_energy); IRP (NIP(FC) = sensor node(fc); Broadcast the IRP packet to neghborng nodes of sensor node. Step7. end

83 61. Data transmsson Ths phase s ntated when a sensor node dentfes user s request and begns to send data to the snk. To begn ths phase, source node constructs data packet shown n Fgure 4.9, and computes energy E DS req, usng Equaton (4.3), whch s requred to forward sensed data of sze DS over a dstance r. The data packet has several felds. The feld task_descrpton ndcates the user s request, Source_d gves the address of sensor node at whch user s request s dentfed, DS Ereq gves the energy requred to transmt the sensory data and Data feld holds nformaton about detected event. Task_descrpton Source_d DS E req Data Fgure 4.9: Format of data packet Upon the recepton of data packet, each IN does the followng: 1. Checks for task descrpton n the ICT. 2. Once the task descrpton matches wth any one of the entry n ICT, the nodes whch are lsted n senders_d lst feld of successful match entry n ICT are consdered for selecton of next hop node. 3. Selects any one node among lst of senders as next hop node based on ther energy and FC status. 4. Forwards data packet to selected node. 5. Increments FC and update current_energy after transmttng data. Above operatons are repeated at each selected router, tll the data packet reaches the snk node. Algorthm 4.2 dscusses the logc behnd the selecton of next router n the NL.

84 62 Algorthm 4.2: Selecton of next hop node Step 1. Begn Step 2. Input: Data packet (DP), ICT, NL, temp_lst, E mn /* temporary lst s smlar to NL holds node nformaton temporarly */ Step 3. Output: selecton of new router Step 4. /* checks for a task descrpton n ICT*/ for all the entres of ICT begn for f ( DP ( task descrpton)) = = ICT (task descrpton) ) goto step 4 else Drop the data packet ; goto step 8; end for Step 5. for each entry n senders_d lst /* fnd the entry n NL and correspondng node entry nformaton s coped nto temp_lst */ temp_lst (node_ Id) = NL(node_d)); temp_lst( Current_energy)= (current_energy)); temp (FC) = temp(fc); end for Step 6. /*Fnd the entry n temp_lst havng small FC value */ f found Select the node as next hop node else / * fnd multple node havng same FC value */ f found Select the node havng more current_energy else /*fnd multple node havng same FC value and same energy level*/ f found Select the node randomly end f end f end f Step 7. /* check,whether energy at selected node drops below the threshold after transmttng data */ E thsh Ecurrent E mn ; DS current Ecurrent Ereq ( current Ethsh E ; f E ) /* search for some other node*/ goto step 6; else forward data packets to selected node end f Step 8. end

85 63 v. Node nformaton updaton Once the sensor node forwards data to selected router, ts current_energy and frequency count values are updated. The FC value ncreases by one and current_energy s gven by If E current E current E DS req E current reaches E thsh, t broadcasts ts status as passve to all ts one hop neghbors and enters nto reduced actvty untl t receves a new E mn value from network admnstrator. By runnng energy effcent resdual energy montorng algorthms [ ] admnstrator can know the energy level across the node. If all nodes reach threshold energy level, new threshold s set at each node by broadcastng new E mn value. Ths enables the nodes to partcpate n data transmsson whch are n reduced actvty mode. 4.5 Performance analyss We have done extensve smulaton usng NS-2 smulator to evaluate the performance and valdate the effectveness of the proposed LBDAR protocol. In ths secton the smulaton envronment, performance metrcs and smulaton results are dscussed. The performance of the LBDAR protocol s compared wth mnmum hop routng [51] and energy aware routng [36] protocol Smulaton envronment Sensor nodes are unformly deployed n a feld of 200m 200m. IEEE s used as the MAC layer protocol. The transmsson range s 40 meters. The whole area s dvded nto 4 quadrants and snk node s placed at the center (100,100). Sensor nodes are assgned wth random ntal energy value rangng from 45j to 50j so that smulaton model can model the actual protocol. The mnmum energy E mn and frequency count are set to 5j and zero respectvely. The sze of IMP, NIP and IRP are 32 bytes, 32 bytes and 64 bytes, respectvely. The data packet sze s 64 bytes.the parameters used n smulaton are shown n Table 4.2.

86 64 Table 4.2 Smulaton parameters Parameter Network feld Values 200 m X 200 m Number of sensors 100 Transmsson range Packet sze (data + overhead) Transmt power Receve power Idle power mnmum energy E mn 40m 128 bytes 0.660mW 0.395mW 0.035mW 5j In order to study the mpact of node densty on the performance of the LBDAR, sensor nodes are randomly placed n a network feld of 200m X 200m rangng from 100 to 500 nodes n the ncrement of 100. Impact of the traffc s observed by varyng number of source nodes rangng from 4 to 20 n steps of 4 n each quadrant. Each source node s assgned wth two unque data names. For example, one of the source nodes n frst quadrant s assgned wth data names such as anmal trackng and pedestran montorng. The IRP s perodcally generated for every 30 seconds wth dfferent task descrpton and njected nto the network from the snk. Set of source nodes whch dentfy the task descrpton start sendng data towards the snk. The ntal orgnatng rate s one packet per second and maxmum orgnatng rate s lmted to 10pps. Packet loss at each hop, due to lnk falure, node falure or congeston s not consdered. Also an assumpton s made that energy expendture ncurred due to control packets s neglgble. These assumptons wll smplfy our understandng of the results. For each smulaton run, mnmum energy E mn s vared and energy across the nodes s measured Performance metrcs Followng metrcs are chosen to analyze the performance of the LBDAR and to compare wth mnmum hop routng and energy aware routng protocols.

87 65 Energy effcency: It gves average remanng energy across the sensor nodes n the network, for every smulaton run; hgher the value, better s the protocol. Network lfetme: It s defned as the length of the tme from the network deployment to frst node drans out of energy among all sensor nodes. Standard devaton of resdual energy e : It gves the average varance between resdual energy level of all nodes and s measured by s 1 e ( E s res 1 res ) 2 where res E and are, respectvely resdual energy at node and mean resdual res energy of all the nodes, and s gves the number of nodes n the network. Therefore e, ndcates dstrbuton of energy consumpton across the sensor nodes. The smaller devaton ndcates that the routng protocol has better capablty to balance energy consumpton across the nodes. Relablty: It s the rato of number of packets successfully arrved at the snk to total number of data packets sent by source nodes. Hence, protocol transmsson effcency s drectly proportonal to packet delvery rato. Standard devaton of Frequency Count f : It gves the average varance between frequency count values of all nodes, where frequency count value at a node gves the number of tmes the node s nvolved n relayng data packets. f 1 s s 1 ( FC FC ) 2 where FC and FC are, respectvely, frequency count at node and mean frequency count of all the nodes, and s gves the number of nodes n the network. Therefore f ndcates dstrbuton of sensor nodes nvolved n forwardng data packets. The routng protocol provdes good chance for all the nodes to actvely partcpate n forwardng data messages by achevng smaller devaton n f.

88 Average remanng energy (joules) Results and dscusson Energy effcency In order to acheve a long-lved network, energy load must be evenly dstrbuted among all sensor nodes so that the energy at a sngle sensor node or a small set of sensor nodes wll not be draned out very soon. Fgure 4.10 shows the average remanng energy across the nodes when node densty N = 500 and E mn =3J. From ths fgure, t s obvous that the mnmum hop routng protocol outperforms the proposed LBDAR protocol and energy aware routng protocol. It s also observed that, the mnmum hop routng saves 19.3% and 30.5% more energy than LBDAR and energy aware routng protocol, respectvely. Smlarly, energy aware routng protocol saves 10.6% energy more than the LBDAR protocol. Even though mnmum hop routng and energy aware routng protocols are achevng hgher energy effcency, these protocols fal to transmt data as the reportng rate ncreases and also, only energy along the optmal path and pre establshed multpath s depleted. However, the proposed LBDAR protocol contnues to transmt data even wth the ncrease of reportng rate and thus dstrbutes the traffc load across nodes and hence dfference of energy level across the nodes s less. 5 4 Data cannot be forwarded E mn =3j, E thsh = 5 - E mn LBDAR protocol Energy aware routng Mnmum hop routng Packet generaton rate (pps) Fgure 4.10: Average remanng energy vs. packet generaton rate

89 Packet delvery rato 67 Relablty The plots n Fgure 4.11 show the comparatve packet delvery rato of LBDAR, mnmum hop routng and energy aware routng. It s observed that LBDAR protocol outperforms the mnmum energy and energy aware routng protocol as the packet generaton rate ncreases. Ths s because the LBDAR protocol explores the path dynamcally and provdes chance to all the routers to actvely partcpate n data forwardng. Also, the LBDAR avods the node falure due to early depleton of energy by employng adaptable threshold energy settng and montorng mechansm, thereby mprovng the packet delvery rato at the snk. In mnmum hop routng, relablty reduces as packet generaton rate ncreases. Ths s due to energy depleton across the nodes whch le on mnmum path resultng n network partton. The results of energy aware routng protocol have ndcated that data has been forwarded contnuously along the suboptmal paths. Eventually energy gets depleted along those nodes and fals to delver the data LBDAR protocol 0.2 Mnmum hop routng Energy aware routng Packet generaton rate (pps) Fgure 4.11: Packet delvery rato vs. packet generaton rate Comparatve analyss of energy effcency and relablty Table 4.3 gves comparatve analyss of average remanng energy and packet delvery rato of each protocol. It s observed that LBDAR sgnfcantly acheves packet delvery rato of about 64.02% and 68% more aganst mnmum hop routng and energy aware routng protocol. It s also observed that, the mnmum hop routng can save 19.3% and 30.5% more energy than

90 Network lfetme (sec) 68 LBDAR and energy aware routng protocol, respectvely. Even though the mnmum hop routng acheves more energy effcency, packet delvery performance of the protocol s low. Table 4.3 Comparson of energy effcency and packet delvery rato Energy effcency Packet delvery rato LBDAR 40.6% 98.67% Mnmum hop routng Energy aware routng 67.9% 34.65% 50.2% 30.67% Network lfetme Ths metrc s an mportant measure of the network survvablty. Fgure 4.12 shows the LBDAR enhances network lfetme on an average 2.5 and 1.5 tmes more than mnmum hop routng and energy aware routng, respectvely. Ths result s acheved by the LBDAR protocol because of ts traffc load dstrbuton and t prevents depleton of energy along optmal path by provdng opportunty to all nodes to partcpate n forwardng of data traffc LBDAR protocol Energy aware routng Mnmum hop routng Intal energy (joules) Fgure 4.12: Network lfetme vs. ntal energy In contrast, both mnmum hop and energy aware routng suffers from reduced network lfetme as compared to the LBDAR. The reason behnd that s, mnmum hop routng uses mnmum path contnuously for data transmsson and hence energy gets depleted along the

91 Standard devaton of resdual energy (joules) 69 nodes n that path and hence the network partton occurs at the earlest tme. Energy aware routng protocol mantans a set of paths and chooses the one based on a probablstc fashon. Once energy along the establshed paths gets depleted, network fals to provde connectvty among the nodes. Standard devaton of resdual energy The graphs n Fgure 4.13 ndcate the standard devaton of remanng energy across the nodes. In order to show the comparatve performance of each protocol, we have executed smulaton runs for varyng node densty rangng from 100 to 500 wth an ntal energy of 5J at each node. The purpose of ths plot s to show that the LBDAR dstrbutes the load more evenly across the network. Thus the dfference n energy usage among nodes s less as compared to mnmum hop routng and energy aware routng protocol as shown n the fgure. Ths s because the LBDAR protocol dstrbutes the total traffc load over spatally dstrbuted nodes by dynamcally constructng path from source to snk for every new data ntaton at source node. Eventually, all nodes are unformly nvolved n data forwardng actvty and thus reduce energy usage dfference across the nodes n the network. In contrast, the average resdual energy varance of mnmum path and energy aware routng protocol ncrease wth the ncrease of traffc densty. Ths s due to contnuous data transmsson over mnmum hop and selected paths whch n turn leads to uneven energy depleton across the nodes. Hence results conclude that the LBDAR protocol mproves the network health. 4 3 LBDAR protocol Mnmum hop routng Energy aware routng Node densty Fgure 4.13: Standard devaton of resdual energy vs. node densty

92 Standard devaton of frequency count 70 Standard devaton of frequency count The plots n Fgure 4.14 show that number of nodes nvolved n data forwardng actvty s more n the LBDAR protocol as compared to other two protocols, because the FC parameter of a node prevents the node from beng chosen as next hop node repeatedly. The FC provdes a chance to all sensor nodes to actvely partcpate n forwardng data messages. As a result, the LBDAR protocol acheves lesser standard devaton of frequency count value than mnmum hop and energy aware routng protocols. From the measurement results, the standard devaton for resdual energy and frequency count of each protocol are tabulated n Table 4.4. Smulaton experment was carred out wth ntal value of FC=15, Energy = 5j and E mn = 1j LBDAR protocol Mnmu hop routng Energy aware routng Threshold=4j Node densty Fgure 4.14: Standard devaton of frequency count vs. node densty Table 4.4 Smulaton results of standard devaton of resdual energy Standard devaton of Standard devaton of resdual energy (E res ) frequency count (FC) LBDAR Mnmum hop routng Energy aware routng

93 Concluson In ths chapter we have dscussed the proposed LBDAR protocol that ensures the survvablty of WSNs. It s data-centrc and reactve-protocol, used for remote-survellance sensor network applcatons. It effcently dstrbutes the traffc load and ensures the unform energy consumpton n the network. By effcently balancng the traffc nsde the network, the network lfetme s sgnfcantly mproved. Extensve smulaton results show that the proposed LBDAR protocol s energy effcent wth respect to extenson of the lfetme of the sensor network substantally compared to other two methods mentoned.

94 CHAPTER 5 DATA QUALITY AWARE ROUTING PROTOCOL Ths chapter dscusses the proposed Data Qualty Aware Routng protocol, called DQAR protocol for relable delvery of crtcal data n WSNs. The DQAR protocol dentfes, prortzes and provdes dfferentated servce to crtcal packets at each router and delvers crtcal data relably to snk or base staton. At the outset, we present the network model, data model and the structure of router nformaton table whch are consdered for the desgn of DQAR protocol, followed by dscusson on approaches for provsonng of QoS n relablty doman and ts workng methodology. 5.1 Network model We consder a general network model shown n Fgure 5.1, n whch large number of sensor nodes are densely deployed nto two dmensonal terran wth sngle base staton v * at the center. The network conssts of two types of sensors: small number of powerful Source Nodes (SNs) and large number of low end Intermedate nodes (INs). SNs are responsble for montorng and ntatng data transmssons whenever an event s detected. INs have two man functons: () route data messages comng from SN or from another neghborng IN () select the next neghbor IN and uncast the receved data, n order to decrease transmsson overhead.

95 73 All nodes are assumed to be statonary, havng communcaton range r and are aware of ther locaton usng any localzaton algorthm. It s assumed that each SN can communcate wth atleast one IN and each IN can have one or more neghbors, some of them could be reached drectly from the snk. Multcast communcaton s used between a source node and ts frst hop INs and Uncast Communcaton s used between INs. Event detected regon v * Intermedate Nodes Source Nodes Fgure 5.1: A typcal wreless sensor network model 5.2 Data model The data traffc generated n the network conssts of dfferent types of packets. The DQAR protocol separates data packets nto three categores and offers dfferentated routng servces to these packets. The frst category conssts of normal packets, tagged as low prorty data (LPD) packets whch nclude regular data packets havng redundant nformaton and other non mportant packets whch are generated at regular ntervals of tme. The second type of packets s called as medum prorty data (MPD) packets and s based on event trggered data. The thrd type called hgh prorty data (HPD) packets generated durng crtcal events and such data packets demand hgh relablty and better qualty of servce.

96 Structure of routng nformaton table Each sensor node mantans nformaton about ts one hop neghbors n a table called Router Informaton Table (RIT). When data needs to be forwarded, sensor node fnds a best next hop router usng RIT. In WSNs, sensor nodes are densely deployed and hence RIT sze s large. However, havng very large RIT n a sensor node s often restrcted by avalable memory. Formng such a RIT n a densely populated sensor network leads to selecton of a router not havng gradent towards the snk and resultng n a route devatng from the optmal path towards the snk. To deal wth ths problem, we propose constructon of a new table called Angle Based Router Informaton Table (ABRIT) to lmt the sze of RIT. In ths secton, a mechansm for constructng ABRIT s dscussed Assumptons Intally all nodes start wth same energy level and a rado range r. S and V denote the set of SN and IN respectvely. x y ( v, v ) represents the x-y locaton of IN v V. A v be the area of the rado range of IN v. SNs are n small numbers compared to number of INs. All SNs and INs are assgned wth unque ID. Data receved by INs s always forwarded to ts downstream nodes. All INs have suffcent memory to store the receved data packet untl they are forwarded to next router. Network model uses multhop transmsson to delver the data to snk.

97 Table constructon mechansm. RIT constructon As soon as the sensor nodes are deployed, at perodc tme ntervals, each node exchanges beacon messages (HELLO_PKT) wth ts neghborng nodes and constructs a RIT. The format of HELLO_PKT s as follows: <Node_d, (x pos, y pos ) > Ths HELLO_PKT ncludes the geographc locaton (x pos, y pos ) of the node and Node_d. Usng HELLO_PKT s, each node starts constructng ts neghbor set N. The neghbor set of node v V s defned as N( v ) { v j V d( v, v j) r, j} (5.1) where d v, v ) s the dstance between node v and v j and gven by 2-D Eucldean dstance ( j d ( v, v j ) ( v x j v x ) 2 ( v y j v y ) 2, for example, the neghbor set of node v 1, n Fgure 5.2, s gven by N ( v 1 ) {1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20}. The neghbor set of a node forms the RIT.. RSA constructon Once RIT s constructed, t s necessary to lmt ts sze. Ths s acheved by constructng a qualfed Router Set Area (RSA) for all the nodes v V. The RSA for a node v s gven 2 by RSA r / 2, where v v v s the routng angle formed symmetrcally around the drect path L. (L s the drect path between the node v and the snk, shown n Fgure 5.2) The routng angle v s specfed by the admnstrator durng node deployment phase. The set of sensor resdng n the RSA of node v forms the Angle Based Router Set of v and denoted as ABRS v.the number of routers n ABRS s based on the routng angle, whch controls the number of routers n the ABRS and always ABRS v N( v ). Example, ABRS {2,4,6,7,9,15} when v v (Fgure 5.2).

98 76 Source Node Intermedate Node Event detected regon 21 v 2 v v 1 12 r v L L v 3 L v 3 v * Base or snk node ABRS v A v Fgure 5.2: Illustraton of constructon of RIT and ABRIT at node v 1, v 2, and v 3 n a sensor network model. Relatonshp between routng angle and routng path length The routng angle specfed by the admnstrator decdes the possble number of routng sensors n ABRS v. Large v wll result n more number of router sensors n ABRSv and route constructon area and hence the routng paths constructed may be longer, leadng to a longer delay. In contrast, smaller v helps to restrct the routng path constructon area and hence control the data delvery latency. As a result, the routng angle v decdes both number of routng sensors n ABRSv and the length of routng paths. Ths type of constructng router set wth smaller v at each node crcumvents the naccuracy of local decson n selectng next router and helps n explorng mnmum latency paths by confnng the paths towards the snk.

99 77 v. ABRIT constructon The nformaton about the nodes resdng n ABRS v are stored nto the table called Angle based Router Informaton Table (ABRIT). The ABRIT for node v 1 s shown n Table 5.1.The entres n the ABRIT conssts of node-d and ther X-Y locaton value. Havng ths type of router set wll restrct the network wde packet floodng and prevents devaton from confned path and always ensures progressng of packets and path dscovery towards the snk. Eventually, paths are establshed wthn the optmal path regon. Optmal path regon s an area that contans the shortest paths from crtcal area to the snk. Havng the ABRIT at each node helps to construct shortest multple paths by confnng paths towards the snk. The packets sent over these paths wll meet the end-to-end deadlne requrements. Table 5.1 Angle based router nformaton table(abrit) Node-d x-y locaton v 2 ( x 2, y 2 ) v x, ) 4 6 ( 4 y 4 v x, ) 7 ( 6 y 6 v x, ) 9 ( 7 y 7 v x, ) ( 9 y 9 v 15 ( x 15, y 15) v. Illustraton For the gven routng angle 0 30, from Fgure 5.3, the ABRIT for some of the nodes are : v {1,2,3,4 }, v {5,6,7,8 }, v {9,10,11,12,13}, v {14,15,16,17}, v {18,19,20,21}, v {22,23,24,25} and v {26,27,28,29,30}. Also, establshment of multple paths wthn the 19 optmal path regon s shown n Fgure

100 78 V Snk or Base staton Source Node Router set area Fgure 5.3: Constructon of ABRIT at each node based on specfed angle Event detected regon Snk node Source node RSA of SN An optmal path regon where all paths leadng towards snk (optmal path regon) Intermedate node Fgure 5.4: Illustraton of establshment of multple path n the optmal path regon 5.4 QoS provsonng approaches n relablty doman Relable delvery of crtcal data s the most prevalent task n wreless sensor network applcatons. To acheve ths task, we propose the followng three desgn approaches:. Dynamc multpath exploraton To acheve desred relablty, redundancy approach s used to transmt data from source to snk n WSN applcatons. To ntroduce such redundances multple path routng mechansms

101 79 are requred. The proposed protocol also employs multple paths approach to acheve redundancy. However, multple dsjont paths are explored dynamcally for every ntated traffc at source nodes wthn the optmal path regon as llustrated n Fgure 5.5. Event detected regon Optmal path regon Snk Intermedate Node Set of Multple paths establshed dynamcally for traffc 1 Set of Multple paths establshed dynamcally for traffc 2 Fgure 5.5: Illustraton of dynamc multpath exploraton for every newly ntated traffc. Hop-by-hop uncastng wth request reply polcy WSNs can employ ether end-to-end or hop-by-hop model to acheve relablty. End-toend relablty model, forces all confrmatons and retransmssons to follow the complete path between source and destnaton, at the expense of already scarce resources such as bandwdth and energy. Hence, achevng relablty on end-to-end bass s nfeasble n WSNs. However, t s a well establshed fact that provdng relablty assurance at ntermedate nodes usng hop-byhop bass s more energy-effcent than treatng relablty as an end-to-end ssue. Relablty can be characterzed by packet delvery rato, whch s defned as the rato of number of unque packets successfully receved by the snk to the number of packets generated by source nodes. For a gven path p, the end-to-end relablty R s dependent on relablty at every hop and can be computed as follows: R ( v, v ) V j r( v, v j ) (5.2)

102 80 Where r v v ) s the relablty of the hop between IN v and v j on path p; snce (, j relablty s multplcatve, a varaton at any one of the hop on p would change the end-to-end relablty remarkably. For nstance, consder relablty requrement of 95%. If relablty at all the hops s below 95%, then relablty degrades consderably and hence event can t be dentfed at snk wth full accuracy whch leads to falure n defensve acton. Even a degradaton of 5% at each hop wll cause a total decrease of 27% on a path p wth 6 hops, and wth ncrease n the number of hops n a path,the end-to-end relablty decreases. Usually the number of hops n large scale sensor networks s much larger than n ad hoc networks. For relable delvery of the crtcal packets at each hop, proposed protocol employs hop-by-hop uncastng wth requestreply message exchange as shown n Fgure 5.6. In ths mechansm a par of request and reply packets, s exchanged between the sender and the selected router before the transmsson of data packets. Source node Snk node Request Reply Intermedate node Fgure 5.6: Illustraton of hop-by-hop uncastng wth request-reply message exchange. Energy reservaton In a WSN, to acheve the relablty and end-to-end guarantee, multpath routng schemes uses pre-establshed multple routes between source and snk. Multple data copes are delvered usng these routes. In ths scenaro, multhop routes can overlap and a partcular node may serve as shared router for varous multple routes orgnatng from varous source nodes. As a result, energy at the shared router gets depleted early whch wll cause a permanent break n the transmsson. Even though the route has been reserved n multpath routng schemes, due to the

103 81 early depleton of energy at the shared router, network fals to delver the crtcal packets to the fnal destnaton wthn the gven tme. To llustrate ths falure, consder the scenaro shown n Fgure 5.7. Pror to the data transmsson, the establshed paths from sources SN 1, SN 2 and SN 3 to snk are SN 1 A C D snk, SN 2 A C D snk and SN 3 B C D snk respectvely. The routers C and D are shared by all the three paths. Here the nodes are selected and reserved as routers wthout the knowledge of ther energy status and amount of data that can be forwarded wth the remanng energy. If the sze of the data stream orgnatng at source SN 1, s greater than the data orgnatng at SN 2 and SN 3, then entre energy at the routers C and D may be consumed by data stream of SN 1. Ths may lead to falure of the nodes C and D, and cause break n the transmsson. As a result the network fals n delverng data orgnated at SN 2 and SN 3, even though the paths are establshed pror to the data transmsson. Hence, we consder that an energy-effcent routng protocol must be aware of energy status. Keepng ths requrement n mnd, t s necessary to allevate delvery falures by reservng energy at ntermedate nodes for the source ntated traffc. Once an IN agrees to relay traffc, the reserved energy s completely dedcated for that transmsson. Subsequent energy requests at the IN from dfferent sources wll be satsfed dependng on the avalable energy at the node. SN 2 SN 1 SN 3 A B C D Snk Fgure 5.7: Illustraton of pre-establshed multpath sharng common routers

104 82 v. Packet schedulng and servcng Traffc n sensor networks s hghly dversfed and each traffc type has unque requrements n terms of relablty and delay. Hence, traffc arrvng at a node s a combnaton of crtcal and perodc data packets. Many of the exstng routng protocols are lackng n dscrmnatng the nformaton based on the contents they forward and use tradtonal Frst Come Frst Serve (FCFS) scheduler to servce the packets, whch leads to starvaton of crtcal packets. If the routng protocol fals to delver such useful nformaton to snk nodes on tme, the snk node wll fal to dentfy the phenomena and may lead to severe causaltes. To address ths problem, proposed protocol mantans a separate queue for each type of traffc and schedules each queue based on ther prorty. As per the assumpton of data model, the proposed protocol categorzes the traffc nto three types based on ther mportance, vz., HPD, MPD an LPD traffc flow and hence, three separate queues are mantaned at each node, as depcted n Fgure 5.8. The classfer classfes the packets and scheduler schedules the queues based on ther prorty. flow 1 flow 2 flow n P A C K E T C L A S S I F I E R HPD Packets MPD Packets LPD Packets Mult Level Queue Scheduler Fgure 5.8: Packet schedulng and servcng 5.5 DQAR protocol Secton provdes a bref overvew of the DQAR protocol. The operatons performed by SNs and INs n routng HPD, MPD and LPD packets are dscussed separately n secton and respectvely.

105 Overvew As soon as crtcal event occurs n crtcal regon, source node detects an event and assgns t as HPD packets. There mght also be several other SNs collectng dfferent types of nformaton from other parts of the network. Ths nformaton s classfed as MPD and LPD packets. If the sensed data s tagged as HPD, SN constructs route request packet and multcast to all INs whch are at one hop wthn ABRIT, whch s shown n Fgure 5.9. Ths leads to exploraton of multple ndependent paths towards the snk. Hence, sensed data s transmtted over multple paths on hop-by-hop manner. At each hop, INs employ hop-by-hop uncastng request-reply polcy wth energy reservaton mechansm to forward the data packets to next selected router. Consder a scenaro gven n Fgure 5.10 to llustrate hop-by-hop uncastng request-reply polcy wth energy reservaton mechansm. In ths mechansm, par of packets such as request and reply packets are exchanged between the sender and the selected router before the transmsson of data packets. In Fgure 5.10, IN A checks for avalablty of requred amount of energy to transmt forthcomng data packets at the selected IN B by forwardng the request packet. If the request s satsfed, B reserves the requred amount of energy and acknowledges the sender A by sendng reply message. In response to reply message, A forwards data packets to B. Snk node Source node RSA of SN A Regon where all paths Intermedate node leadng towards snk Fgure 5.9: Illustraton of exploraton of multple paths for HPD packets and devaton of path from optmal regon for LPD and MPD packets

106 84 D A B C Request Reply message Reply error message Depleted energy Remanng Energy Reserved Energy Energy not avalable Fgure 5.10: Illustraton of hop-by-hop uncastng wth energy reservaton Ths knd of data transfer wll provde energy assurance for forthcomng data packets and thereby mtgates loss of packets due to lack of energy and thus mproves relablty at every hop. Further energy requests at IN B from dfferent sources wll be satsfed dependng on the avalable energy level at node B. Smlarly, IN B also fnds the next IN whch satsfes the request. Whle transmttng data over INs, each IN prortzes and forwards only HPD traffc towards snk. However, for MPD and LPD packets, SN uncasts the data to next IN whch doesn t belong to ABRIT, so that, the path s devated from optmal path regon and thus reduces the transmsson overhead, as shown n Fgure 5.9. In ths protocol, the ERREQ (Energy Reservaton Request) packet and Aerr/Ardy packet take the defnton of request and reply packets, respectvely. The format and feld specfcatons of ERREQ are detaled n secton Dfferentated servce at source nodes Whenever SNs detect the phenomenon, prorty level P l, of the detected event s to be dentfed. Identfyng the crtcalty of data s beyond the scope of ths thess and t s a separate research ssue. Here, an assumpton s made that source nodes are equpped wth sutable prorty computaton algorthm whch dentfes the type of detected event. Once prorty s computed, SN constructs ERREQ and data packet n the formats shown n Fgure 5.11 and 5.12, respectvely.

107 85 Type=0 DS E source_d sender_d P Tot l NP Fgure 5.11: Format of ERREQ packet Type=1 source_d P l Data Fgure 5.12: Format of Data packet In ERREQ packet, the feld E DS Tot, gves the total energy requred at an IN to transmt and receve data of sze DS, NP gves the total number of packets, source_d gves the address of the source from where data packets orgnated, the sender_d s the address of forwardng node and prorty level P l, takes the value ether HPD/MPD/LPD based on the nput receved by prorty computaton algorthm. The felds source-d and P l n data packet takes the meanng of correspondng felds n ERREQ packet. The data feld holds the data to be forwarded towards the snk. The Type feld value s 0 n ERREQ and 1 n data packets. Algorthm 5.1 s developed to construct request packet, data packet, and assgnng the prorty levels to the detected event. Step 1. Step 2. Step 3. Step 4. Step 5. Step 6. Step 7. Step 8. Algorthm 5.1: Constructon of ERREQ, data packet and assgnng prorty Begn Input: Prorty and sensed data Output: Request and Data packet r communcaton range Compute the sze of the sensed phenomena DS sze of ( sensed phenomena) NP Number of packets E DS Tot Compute Energy, requred to transmt data of sze, DS, over one hop dstance, d <= r usng frst order rado model DS ETot ETx ( DS, d) ERx( DS) Compute the prorty level, P l based on crtcalty f tag = LPD then P l =00 f tag = MPD then P l =01 f tag = HPD then P l =11 Construct ERREQ packet by embeddng Type=0; NP, sender_d n ther respectve felds DS E Tot, P l, source_d,

108 86 Step 9. Construct the Data Packet by embeddng type=1; source_d ; P l, data; nto ther respectve felds. Step 10. f P l = =11 then {Broadcast ERREQ packet to the routers belongs to ABRIT} end f Step 11. f P l = 00 or P l = 01 then Uncast the data packets to the selected router whch doesn t belong to ABRIT end f Step 12. end Dfferentated servce at ntermedate nodes IN receves dfferent types of packets such as data packets, ERREQ packet from ther upstream neghbors and Ardy /Aerr reply packets from ther one hop downstream neghbors. In order to provde dfferentated servces to the arrved packets, we propose the archtecture for INs at network layer and s shown n Fgure PACKETS P A C K E T C L A S S I F I E R Data Packets ERREQ Packet Ardy / Aerr P A C K E T C L A S S I F I E R D U P L I C A T E V E R I F I E R HPD-QUEUE MPD-QUEUE LPD-QUEUE M U L T I L E V E L Q U E U E S C H E D U L E R Data Packet Forwardng Unt (DPU) HPD/MPD /LPD/Packet Request Packet Processng Unt (RPU) ERQUEUE Packet analyzer and Forwardng Unt (PFU) HPRIT ABRIT Energy Reservaton Unt (ERU) EC Src-d S1 S3 Yes Selected router d IN3 IN5 Reserved energy Remanng energy SEL node-d IN1 IN5 Router Selecton unt (RSU) Acknowledgement Handler (AH) RES/NRES X-Y Value 100, ,160 IN3 100,130 Forward data packet to selected router Forward ERREQ Packet to a randomly selected router Ardy / Aerr to sender Fgure 5.13: Proposed archtecture at ntermedate nodes to provde dfferentated servces