SENSORCOMM 2012 : The Sxth Internatonal Conference on Sensor Technologes and Applcatons A Relable and Real-Tme AggregatonAaware Data Dssemnaton n a Chan- Based Wreless Sensor Network Zahra Taghkhak, Nrvana Meratna, Paul J.M. Havnga Pervasve Systems, Unversty of Twente Enschede, Netherlands (z.taghkhak, n.meratna, p..m.havnga@utwente.nl Abstract Tme-crtcal applcatons of Wreless Sensor Networks (WSNs demand tmely data delvery for fast dentfcaton of out-of-ordnary stuatons and fast and relable delvery of notfcaton and warnng messages. Due to the low relable lnks n WSNs, achevng real-tme guarantees and provdng relable data s qute challengng. To ensure data relablty, tradtonally varous retransmsson mechansms have been used, whch n turn ntroduce extra delay. In ths paper, we propose READ,.e., a relable and realtme aggregaton-aware data dssemnaton to ensure relable and fast data delvery n a chan-based WSN. We also nvestgate the relatvely unexplored topc of mpact analyss of Tme To Lve (TTL and lnk relablty parameters on network performance n terms of attaned ht rato for three dfferent approaches,.e., READ, QoS-ACA, and the stop-andwat (S-W ARQ to assess the approprateness of each method facng dfferent condtons. The smulaton results show READ performs better n terms of ht rato compared wth QoS-ACA and S-W ARQ when lnk relablty s low and packet's TTL s short. Although not beng the prmary goal of READ, energy consumpton of the protocol s also much lower than the other two approaches. Keywords- Chan-based wreless sensor network, relable/real-tme data dssemnaton. I. INTRODUCTION Wreless sensor networks are one of the most promsng technologes for applcatons such as structural health montorng. Montorng operatonal performance of large cvl engneerng (nfrastructures such as brdges, tunnels, hghways, and water ppes requre deployment of long lnear arrays of sensor nodes. As the length of these (nfrastructures s often much greater than ther wdth, ther topologes resemble a long chan. Long lnear chan-type sensor networks have often a large number of hop counts and to operate for a long tme, they usually need to work on a low duty cycle. The large number of hop counts challenges exstng data dssemnaton protocols already desgned for wreless sensor networks, whle the low duty cycle ntroduces extra delays. Tme-crtcal applcatons such as dsaster management and structural health montorng hghly depend on the avalablty of real-tme data as n these applcatons data s nether useful nor valuable f t s receved after ts Tme To Lve (TTL. Outdated data s not only be useless but also harmless as t may have negatve mpacts on the decsons made by provdng nvald nformaton. Moreover, transmttng expred data depletes the energy of relayng nodes napproprately. Due to ther poor lnk qualty, provdng real-tme guarantees and data relablty n WSNs s qute challengng. Lnk qualty can be easly affected, among others, by weather, temporary obstacles, and moblty. Most of exstng real-tme algorthms appled n other networks than WSNs assume network s relable and packets are not lost because of low lnk qualty. Therefore, they cannot be drectly appled to WSNs. The hgher the packet loss due to low qualty lnks, the lower the performance of a real-tme wreless sensor network. One of the mechansms to provde data relablty s through ntroducton of redundant data by transmttng the same data multple tmes, whch results n hgh energy consumpton. It s somewhat clear that ensurng relablty may not always go hand n hand wth ensurng network lfetme. Dependng on the applcaton at hand, one can also argue that energy effcency, real-tmeness, and data relablty are not always equally mportant. Data relablty and real-tmeness become sgnfcant for applcatons dealng wth dentfcaton of outof-ordnary stuatons as well as warnng and notfcaton systems, whle contnuous montorng applcatons demand long network lfetme and can tolerate latency and data unrelablty to some extent [1] by usng local technques such as flterng and anomaly detecton. In the latter applcatons, data aggregaton s consdered as a sgnfcant prmtve, whch not only helps save energy and bandwdth by communcatng less data but also provdes meanngful nformaton to the end-users. The man problem addressed n ths paper s the desgn of an aggregaton-aware data dssemnaton protocol for a chan-based WSN sufferng from low relable communcaton lnks whle satsfyng the delay and relablty requrements of the packet. Unlke exstng technques, our proposed protocol combnes real-tme and relablty guarantees for each packet and ncreases ht rato (the percentage of the packets receved by the base staton before ther deadlne expre. To deal wth the energy consumpton and to enrch data, we utlze data aggregaton on the ntermedate nodes as far as t does not nfluence packet deadlne. We also nvestgate the relatvely unexplored relatonshp between the TTL and lnk relablty parameters and ther mpact on the ht rato for three dfferent approaches,.e., READ, QoS-ACA [2] and an ARQ approach, to assess the approprateness of each method facng dfferent condtons. The rest of ths paper s organzed as follows. Frst we brefly dscuss state of the art and prelmnares of ths study. Then a detaled descrpton of our proposed approach wll be Copyrght (c IARIA, 2012. ISBN: 978-1-61208-207-3 260
SENSORCOMM 2012 : The Sxth Internatonal Conference on Sensor Technologes and Applcatons provded, whch wll be followed by performance evaluaton. Fnally we draw some conclusons and future works. II. RELATED WORK Several data aggregaton protocols have been proposed for WSNs n the past. However only a very few of them consder both relablty and tmelness and am to ensure them smultaneously. Real-tme guarantees are usually provded through ether real-tme schedulng or real-tme routng. SPEED [3] s a well-known protocol addressng soft real-tme guarantee n WSNs n such a way that packet deadlne s mapped to a velocty requrement. The node wth a velocty hgher than the specfed requrement s more lkely to be chosen as the upstream node. MMSPEED [4], s an enhanced verson of SPEED ams to meet relablty and tmelness requrements together whle utlzng multpath routng to handle relablty such that number of path s n drect proporton to the requred relablty. Tmelness s supported by combnng the SPEED dea wth packet prortzaton, whch s done on the bass of the requred speed for each packet. R2TP [5] proposes a relable and realtme data dssemnaton, n whch relablty s satsfed by sendng several copes of one packet through multpath such that sum of the relablty of the consdered path s equal or hgher than the requested relablty. Ths packet s dropped by the ntermedate nodes f the elapsed tme of a gven node s greater than the delvery tme requrement. Otherwse, t forwards that packet through mult paths usng the gven node s table, whch stores the delay of dfferent paths. Soyturk et al. [6] present a relable data acquston approach for tme-crtcal applcaton of WSNs. Relablty s provded smlar to technques of [4][5] leveragng multpath approach whle real-tme concern s supported by packet prortzaton. Ths technque therefore deals wth the prorty schedulng to handle queung delay, whch s of the man causes of makng end-to-end latency. Almost all of the aforementoned relable approaches support relablty by sendng several copes of a packet through dfferent paths. To the best of our knowledge, there s no well-explored work to address these two qualty of servce (QoS parameters together n a chan-based WSN, n whch only one path can be establshed between source and destnaton nodes. Moreover, snce approaches of [4][5] are proposed for data dssemnaton rather than data aggregaton, they must employ other methods to flter out redundant data n case of avalablty of duplcate senstve aggregaton functons lke sum or average. QoS-ACA [2] ams to fast, relably, and energy effcently aggregate data n a chan-based WSN and send the aggregated value to a base staton. To ensure relablty, t leverages the benefts of retransmsson wthout usng any acknowledgement (Ack. It utlzes the optmum number of retransmsson to ensure the requred relablty. It consders the resdual and requred energy of each sensor node and the dstance between node and the base staton as two man crtera to select a node as an aggregator. However, t does not guarantee delvery of a packet to the base staton wthn ts deadlne. A. Qualty of Servce Parameters An ncreasng number of WSN applcatons requre realtmeness as ther QoS parameter. Applcatons may have one of the followng four notons of tme: Tme-unrestrcted: whch ndcates no dedcated deadlne exsts and applcaton at hand s not tme crtcal. Soft Real Tme (SRT: based on whch the usefulness of a packet receved after ts deadlne decreases, whch n turn results n a graceful degradaton of the performance. SRT-based approaches am to reduce deadlne mss rato of the packets and are common n WSN because of the unpredctablty nature of these networks. Frm Real Tme (FRT: on whch, the usefulness of a packet receved after ts deadlne s Zero. FRT methods can tolerate nfrequent deadlne msses. Hard Real Tme (HRT: HRT applcatons hghly rely on recept of all packets before ther deadlne ends. Another QoS parameter requrement of many WSNs applcatons s relablty. One commonly used approach to ensure relable data delvery n a falure prone envronment s sendng several copes of one packet from a sngle source node towards the destnaton node. To know whether data s receved by the destnaton, one of the followng technques s used: Sendng an acknowledgement: n ths technque f the acknowledgement packet s lost due to lnk/network falure, source node contnues sendng copes of the receved data, whch leads to hgh energy dsspaton. Sendng multple copes wthout sendng any acknowledgement: although ths approach reduces the acknowledgement overhead, t requres a soluton to ensure data reach to the destnaton after sendng n copes of a packet. B. Duty-cyclng Effcent energy consumpton has one of the hghest prortes n WSNs to ensure long network lfetme. As one of the most energy-expendture operatons s transmttng data, each sensor node must turn ts rado off and goes to asleep state most of the tme to obtan sgnfcant energy savng. In a duty-cycle-based power management scheme, each sensor node goes to sleep and wakes up perodcally. The proporton of the tme that each sensor node spent n sleep mode has drect mpact on the data delvery delay, packet loss, and throughput. The shorter the duty cycle, the lower event detecton probablty and the longer detecton delay. In a schedulng scheme, a sensor node s allowed to swtch between three operaton modes: Sleep mode: whch results n low power consumpton. In ths state the rado of a node s turned off but the sensors may be operatonal. Actve mode: whch tself ncludes two operatonal states: recevng state (RX, and transmttng state (TX. III. PRELIMINARIES The prelmnares of ths study s presented here. Copyrght (c IARIA, 2012. ISBN: 978-1-61208-207-3 261
SENSORCOMM 2012 : The Sxth Internatonal Conference on Sensor Technologes and Applcatons Idle state: n whch rado s ready to receve or transmt data. Accordng to the condtons the rado s changed to the approprate actve state. Fgure 1 presents the state dagram llustratng the man states of the rado and the ways state transtons occur. Once the sleepng tme(ts s over, the rado must undergo a transton to dle state. On the other hand, the rado of a node must be swtched to off as soon as the actve tme (TA s fnshed. It s worth notng that these four states have dfferent levels of energy consumpton, whch dffer from one rado model to another. Fgure 1. State dagram for rado states C. Network Model We make the followng assumptons regardng the WSN. The WSN conssts of N sensor nodes deployed n a lnear topology and two base statons are located at two sdes of the chan. We have descrbed n [2] a mechansm usng whch a chan leader can be selected through whch sensor data s forwarded to the base staton. In case of not beng a chan leader, sensor nodes can only communcate wth ther drect neghbors. The locaton of sensor nodes and the base statons are fxed and are known a pror. We have chosen for ths network model as ths s the case n many structural health montorng applcatons. In these applcaton, sensor nodes are placed at known and fxed locatons (for nstance, at crtcal locatons n a long lnear array topology and send ther data perodcally or upon detecton of abnormal stuatons va relayng nodes to a base staton. It should be noted that we assume the packet loss probablty of each lnk s almost fxed and does not change much. Ths s ustfed by the fact that we am to fnd the relatonshp between TTL and lnk relablty wth the network performance. We are aware that lnk relablty changes frequently n practce. In our ongong work, therefore, we enhance READ by consderng dynamc changes of lnks relablty. As far as ths paper s concerned fndng the relaton between TTL and lnk relablty wth the network performance requres a fxed lnk relablty to be assumed. Every sensor node n a chan must send ts data to ts upstream neghbor whch s selected n the chan constructon phase. Intermedate nodes along the path to the chan leader aggregate the data receved from the downstream nodes wth ther own data and forward the local aggregated value towards the chan leader. The chan leader, also called the aggregator, must perform fnal aggregaton on the data receved from two sdes of the chan and then forward the result to the base staton drectly. To motvate the need to address both data relablty and real-tmeness n our protocol, let us consder the network llustrated n Fgure 2, whch conssts of sx sensor nodes such that one of them s selected as the chan-leader and a packet, whose TTL s 10s, should be forwarded from S towards the leader. Let us assume that tme requred to 0 delver a packet from S 0 to the leader s 3s and from the leader to the base staton s 1s. Clearly, ths packet wll be receved by the base staton after 4s. Ths mples that 6s from ts TTL s remaned, whch can be exploted to acheve hgher network performance. We can spend ths tme for ether ( ncreasng aggregaton degree of the leader or ( mprovng transmsson relablty of the network. If the network has hgh relable lnks and t s almost guaranteed that the packet s receved by destnaton through the frst transmsson, t s better to spend ths remanng tme for the aggregaton process and to ncrease aggregaton degree of the leader. In ths case, leader can put the receved packet on hold and perform aggregaton on other packets whch are on the way and wll be receved wthn lmted tme duraton of the watng packet. The remanng TTL tme can also be used to mprove transmsson relablty by utlzng a retransmsson mechansm and sendng several copes of the gven packet. Ths s partcularly useful when network suffers from packet loss. S0 S1 S2 Ldr S 4 S5 Fgure 2. An example of a chan based network D. Polces regardng Relablty and Real-Tmeness To cope wth unrelablty of the lnks, ths paper leverages the beneft of retransmsson approaches wthout usng acknowledgement n order to support relable transmsson. Therefore, smlar to QoS-ACA, we are gong to estmate the optmal number of retransmssons for each lnk. Each sensor node sends multple copes of the same packet to ts upstream neghbor n order to mprove transmsson relablty. Snce recevng a packet after ts deadlne s not only useless but also depletes energy. It s hghly preferable to drop such packets to prevent wastng energy of the ntermedate nodes relayng the packet. Snce the retransmsson mechansm used n QoS-ACA mposes extra delay, we modfy t to meet a gven latency requrement by retransmttng as far as packet s deadlne s not expred. A key queston here s how to assgn the remanng TTL of a gven packet to relayng nodes for ther retransmsson or n another word for how long a packet can be delayed on the ntermedate nodes so that the relablty gan and on-tme end to end delvery rato can stll be maxmzed. We answer ths queston by allocatng the avalable packet s TTL proportonately to the packet loss probablty of the lnks along the forwardng path to udcously and farly use the packet s TTL on ntermedate nodes n such a way that relablty gan and on-tme end to end delvery rato s maxmzed. Copyrght (c IARIA, 2012. ISBN: 978-1-61208-207-3 262
SENSORCOMM 2012 : The Sxth Internatonal Conference on Sensor Technologes and Applcatons IV. DETAILED DESCRIPTION OF READ PROTOCOL Our algorthm starts wth chan constructon usng PEGASIS algorthm proposed n [7]. In a gven chan, one node must be selected as the leader n order to do the fnal aggregaton and to send the aggregated result to the base staton. Two QoS parameters,.e., relablty and energy consumpton as well as two assgned weghts, are consdered to make dfferent crtera for electng a leader. To ths end, we ntroduce the followng formula: T R B ( S ( B ( S ( B ( S B B E R ( S ( InEg (S EER ( S CL 1 N 1 CL k k (S W RsdEg( N 0 1 1 CL E R w E S RqEg EER(S HHR ( S HHR ( S k k (S,S k 1 k 1 CL CL Where S represents a set of sensor nodes, whch are able to drectly communcate wth one of the base statons and CL represents the canddate leader. The hop-by-hop relablty (HHR between two sensor nodes are obtaned usng HHR ( S 1 1 p pktloss ( S 1. By havng the hop-by-hop relabltes, base staton must evaluate the approprateness of each member of Sto be an aggregator. To ths end, base staton frst calculates the endto-end relablty from each sensor node to the desgnated leader by employng (4. At the second step, base staton fnds the beneft of each canddate leader n terms of R relablty ( B by averagng sum of the end-to-end relablty of each sensor node to the desgnated leader usng (3. Ths selecton ensures the maxmum relablty that ths chan can provde. Base staton also fnds the beneft of each E canddate leader n terms of prolongng lfetme ( B usng (2 where RsdEg( S denotes resdual energy of S, InEg( S s ntal energy of S and RqEg( S denotes the requred energy of S f beng selected as the leader. After fndng all the beneft values n a chan, base staton selects the sensor node, whch provdes the maxmum beneft as the leader for a gven chan usng (1. The hgher the beneft value of (1, the hgher the probablty of beng selected as a leader. One should note that aggregaton takes place at dfferent locatons of the network as the leader selecton process results n selectng an aggregator n a dynamc way based on the energy and relablty parameters. Due to applcaton specfc nature of WSN, dfferent applcatons have dfferent requrements. Therefore, assgned weghts (w to each QoS parameter of (1 can be changed n order to satsfy the applcaton requrements. As we have two base statons, two chan leaders can be selected such that they can communcate wth one of the base statons drectly. Sensor nodes must select one of these chan leaders to send ther data to. Ths selecton s done by consderng dstance between sensor nodes and the chan leaders. To fnd out optmal number of copes whch must be sent through each lnk, we follow the followng steps: Each sensor node must update packet TTL employng (5 where TT (Transmsson Tme denotes the tme requred to transmt one packet to the upstream node. TTL Sourcenode PacketTTL (5 TTL TTL 1 C 1 TT LID TTL TTL 1 C 1 TT LID Where: 0 C n Usng (5, requred tme to send C copes of a packet from one node to ts upstream node s subtracted from the TTL of the packet where LID represents leader ID. As we do not know whch packet copy s receved frst, upstream node by lookng at the copy number of the packet can easly recognze C. In the next step, the chan leader assgns a porton of the remanng TTL of the packet to each node by dvdng the packet loss probablty of the lnk adacent to a gven node by sum of the packet loss probabltes of the lnks located between the gven node and leader. Equaton 6 calculates optmal number of packet copes for each node to meet deadlne requrement of the packet. The second term of (6, put an upper bound for the number of packet copes for each lnk only by lookng at the packet loss rate of the gven lnk and the relablty requested by the applcaton. 1 RqRl n mn( n, log PL ( S n PL ( S LID LID PL ( S, BS, BS PL ( S 1 LID 1 LID 1 1 PL ( S, BS PL ( S PL ( S 1 1 TTL TT TTL TT new new LID LID Where S represents the upstream node of 1 S n the chan and PL(S,S 1 denotes the packet loss between S and S. Equatons 5 and 7 can be used f rados of all 1 nodes are never turned off. As we also consder duty cyclng n order to save energy, (7 requres sgnfcant revsons to nclude sleepng tmes whch greatly nfluences remanng TTL of the packet. Therefore, the way we calculate the optmal number of packet copes changes. We assume that the duty cycle of the node s n such a way that f one node sends the frst copy of the packet to ts upstream node, t s awake at that tme but t s lkely the upstream node goes to sleep mode before fnshng transferrng all copes of a gven packet. Therefore, we frst should fnd the number of tme slots n one awake tme perod (ns by havng transmsson Copyrght (c IARIA, 2012. ISBN: 978-1-61208-207-3 263
SENSORCOMM 2012 : The Sxth Internatonal Conference on Sensor Technologes and Applcatons tme (TT of one packet and awake tme perod ( AwT usng AwT. It s worth notng that havng duty ns TT cycle (DC and toggle perod (TP, the AwT can be calculated easly as AwT TP DC. Then we need to calculate number of tme slots that each packet requres (rs to be able to transmt all ts copes along the path towards the base staton. As we are allowed to send (or receve each copy of one packet n one tme slot, the number of tme slots corresponds to the number of packet copes. Therefore, havng requred tme slots for a gven TTL s enough to know the number of packet copes whch must be transmtted to ncrease relablty whle TTL requrement of the packet s met. To fnd rs, frst we need to calculate the number of requred awake cycle (nrc to transmt all packet copes through dfferent nodes usng (8 whle AsT represents the tme the node s n sleep mode. nrc TTL ns TT AsT Where: AsT TP ( 1 DC (9 Each tme slot for a gven node represents one recept or one transmsson for that node. Leveragng (8, (9 and (10, requred tme slots (rs for the gven packet s calculated. Actually, source node usng (10 descrbes the TTL of a packet n terms of tme slots. rt TTL ( ns TT AsT nrc (10 rt rs nrc ns (11 TT Where rt denotes remanng tme of the packet after usng nrc awake cycles to transmt packet copes. Then, the optmal number of sent copes for node S to meet deadlne requrement of the packet by consderng the packet loss probabltes of the upward lnks can be obtaned by (12. The frst term of the rght part of (12 represents the porton ( Ptn of S from TTL remanng of the packet. n PL ( S n PL ( S 1 RqRl mn( n, log (12 LID LID PL ( S, BS, BS Where: ls 0 C 1 LID 1 PL ( S, BS 1 LID 1 SourceNode PL ( S 1 PL ( S PL ( S rs, n 1 1 1 ls ls ls ls 1 LID LID C 1 (8 (13 Here n represents the number of copes of a gven packet whch should be transmtted by the node S. Each sensor node upon recevng a packet must also update remanng or left tme slots ( ls of the packet employng (13, usng whch requred tme slots to send C copes of a packet from one node to ts upstream node s subtracted from the avalable tme slots of the packet. Fgure 3 shows the psuedocode of READ protocol. V. PERFORMANCE EVALUATION We used Java JDK 6 to mplement all algorthms and the smulaton envronment. We perform smulatons for dfferent TTL, lnk relablty and duty cycle values. Each smulaton s executed 100 tmes. In ths secton we am to compare READ, whch employs retransmsson mechansm wthout any Ack whle keepng an eye on packet s TTL remanng tme, wth ( QoS-ACA, whch s also a retransmsson mechansm wthout Ack whle gnorng TTL parameter and ( S-W ARQ, whch s a retransmsson mechansm wth Ack. Tradtonal acknowledgement protocols, namely, stop-and-wat (S-W, go-back-n (GBN, and selectve repeat (SR [8][9][10], try to retransmt one erroneous frame regardless of the lnk relablty state. We compare our method wth a hop by hop S-W ARQ whch s a well-known ARQ scheme. We consder ht rato and energy consumpton as performance metrcs. Ht Rato s defned as the percentage of the packets receved by the base staton before ther deadlne expre. We am to fnd out the relatonshp between dfferent packet loss probabltes and varous TTL values wth the ganed network performance for these three approaches n order to know n whch condton whch method should be employed to provde relablty and real-tme concerns smultaneously. A. Descrpton of scenaros For smulaton, a chan of sensor nodes s formed consstng of 51 sensor nodes randomly dstrbuted n a lnear topology. Two base statons are located one hop away from the rghtmost and the leftmost nodes of the chan. The output power of our rado model (TICC2420 s programmable n eght levels (from approxmately 25 to 0 dbm. Therefore, every sensor node n case of beng a leader utlzes the hghest power level to provde the longest transmsson range, otherwse the mnmum power level whch s requred to reach the closest neghbor s employed. We change the packet loss probablty ( p on the lnks from 0.01 to pktloss 0.9. In all smulatons, the frst man source node s the mddle node of the chan ( S 25, whch must select ether the left sde or rght sde leader towards whch t transmts ts data. Ths selecton s done by lookng at provded delay whch s n drect relaton wth the lnk relablty and dstance. The second and the thrd source nodes are the leftmost and the rghtmost nodes n the chan. The toggle perod (TP s 1500 ms and energy threshold ( s 0.1. Copyrght (c IARIA, 2012. ISBN: 978-1-61208-207-3 264
SENSORCOMM 2012 : The Sxth Internatonal Conference on Sensor Technologes and Applcatons Intalzaton 1. Construct chan usng PEGASIS 2. Fnd S { S S s n Commucat on range of BS} 3. Leader { S S S & best satsfy Equaton1} 4. Duty cyclng schedule; 5. Ptn { ptn ptn s porton of S from TTL} 6. ( Ptn, LID BS S LID 7. ( Ptn, LID S LID S LID 1 LID 1 8. S receves ( Ptn, LID 9. Repeat { Repeat { S sends ( Ptn, LID } untl ( S receves 1 ( Ptn, LID 1 and go to step 9} untl ( receves ( Ptn, LID S READ Protocol 1. f (event detected by S S calculates n usng equaton 12 2. f (( S LID { a. Repeat {} untl ( State S 1 Awake b. numberofse ntcopes 0 c. ( Data Repeat { S S 1 numberofse ntcopes d. } untl (( State S 1 Asleep or ( numberofse ntcopes n e. f ((( State( S 1 Asleep and ( numberofse ntcopes n {Repeat {} untl ( State S 1 Awake ; Go to step 2.b }} 3. else f (( S LID { a. S 1 BS; Run step 2.b to 2.d b. f ( RsdEg LID InEg LID { ( he { S S S & RsdEg InEg} } c. f ( he { for (each S S { InEg RsdEg } d. Go to 3.b} e. else { BS fnds another leader based on Equaton 1} 4. f ( S1 receves Data 5. { AggData 1 Aggregate ( AggData, Data 1 Data AggData ; 1and go to step 2} 1 1 Fgure 3. Pseudocode of READ The results of two duty cycles, 0.99 (rado s almost always ON and 0.1 (rado s almost always Off are represented n ths paper to better udge about duty cyclng mpacts. The other smulaton parameters are lsted n Table I. TABLE I. SIMULATION PARAMETERS No. of nodes 51 Area sze 1m x 260m Mac layer IEEE 802.15.4 Transmt bt rate 250 kbps Operaton frequency 2.4 GHz Packet sze 128 bytes Rado model TI CC2420 Transmt current at 0dBm 17.4 ma Transmt current at -25dBm 8.5 ma Receve current 18.8 ma Supply voltage (1.6 2.0 V Idle current 0.426 ma Transmsson range 10-90 m Recever senstvty threshold -95 dbm B. Performance Evaluatons 1 Ht Rato The acheved ht rato s plotted for these three methods when the Lnk Relablty (LR=1-PacketlossProbablty can be selected randomly from a set of ntervals shown n Fgure 4 and duty cyclng s 0.1. Fgure 4 llustrates attaned ht rato as the packet TTL ncreases from 80 to 3200 ms. It can be seen that ht rato of READ s hgher than S-W ARQ when the lnk relablty n the chan changes randomly between 0.1 and 1 or between 0.4 and 1. READ also outperforms QoS-ACA when TTL of the packet s small (smaller than 1500ms. It can be seen from Fgure 4 (mddle and bottom that when the lower bounds of lnk relablty and TTL are ncreased, performance of S-W ARQ mproves. We can conclude that f both lnk relablty and TTL of the packet are qute hgh, performance of all three technques n terms of ht rato s the same. Otherwse, READ outperforms S-W ARQ and outperform QoS-ACA n case of havng short TTL. To have a better udgment about the exact relaton between TTL of the packet and lnk relablty wth attaned ht rato, n the followng graphs the lower bound of the lnk relablty nterval s ncreased from 0.1~0.97 that means the relablty of a lnk should be hgher than the gven lower bound. Fgure 5 llustrates the ht rato graphs of two dfferent duty cycles for these three approaches. The left sde graphs show mpact of duty cycle 0.99 on ht rato whle the rght sde graphs are for duty cycle 0.1. From Fgure 5, one can see that when ether TTL s short or lnk relablty s low, READ has better ht rato. But when TTL s long and lnk relablty s qute hgh (TTL>1500, LR>0.8-W ARQ outperforms READ because t has enough tme to utlze acknowledgment and also because of hgh relable lnk, packets are almost never lost. Although, the ht rato of READ n these condtons (TTL>1500, LR>0.8 are almost 1 but t has a lttle fluctuaton between 0.97 and 1. It s worth notng, the sharp changes seen n rght sde graphs of Fgure 5 when TTL s about 1500ms are because of usng duty cyclng for sensor nodes. In case of S-W ARQ, one node Copyrght (c IARIA, 2012. ISBN: 978-1-61208-207-3 265
SENSORCOMM 2012 : The Sxth Internatonal Conference on Sensor Technologes and Applcatons requres to frequently swtch between sendng and recevng mode to be able to handle sendng a packet n one tme slot and recevng (or watng to receve correspondng acknowledgement n the next tme slot. Therefore, half of tme slots n one awake tme perod are used for the acknowledgement. Ths s not the case for READ or QoS- ACA approaches. READ and QoS-ACA utlze all tme slots for sendng several copes of the packet. The hgher TTL, the greater number of awake cycles every node s allowed to utlze to send packet and receve acknowledgement n order to ensure relablty whle packet TTL has not yet been expred. READ and QoS-ACA also undergo these sharp changes when duty cycle s too small (.e. 0.1 as they cannot send all packet copes n one awake cycle that s about 150ms and they have to wat for another awake cycle(s to be able to send rest copes. When TTL rased to 1500ms (whch s start pont of another awake cycle, the rest copes can also be sent and the ht rato suddenly mproved especally n case of hgh relable lnks. Also, compared wth QoS-ACA, READ has better ht rato when TTL parameter s short (shorter than 500 ms. In ths case, QoS-ACA sends several copes of a packet, especally when LR s low. QoS-ACA satsfes the requred relablty for the gven packet only for the frst few hops, n whch the packet has not yet been dropped due to TTL expraton. Also, QoS-ACA outperforms RRDA when TTL s greater than 500ms and lnk relablty s lower than 0.3. Ths s due to the fact that RRDA has to be determnstc for supportng real-tmeness and hence always ponders the worst case (longest delay whch means every packet may reach (f t could reach ts upstream node on the last retransmsson. Therefore, downstream nodes cannot delay one packet more than the tme s assgned to them. But t s also lkely that the packet s receved by an upstream node before n retransmssons. Therefore, the downstream nodes could spent ths extra tme for ther own beneft and do more retransmsson whle meetng the packet deadlne. QoS-ACA explot ths fact n order to ncrease ht rato n case of large TTL and low lnk relablty. 2 Energy Consumpton Fgure 6 provdes a comparson between useful energy consumpton (energy spent for packets receved before ther expraton and total energy consumpton for these three relable approaches and for two duty cycles 0.99 (rght graphs and 0.1 (left graphs. It s clear that there s almost no dfference between useful and total energy consumpton for READ, as t drops packets whch are more lkely not to reach the base staton on tme. As llustrated n Fgure 6, READ s much more energy effcent than QoS-ACA and S- W ARQ partcularly n case of low relable lnks and short TTL. The reason for ths s that n case of low relable lnks, data packets or acknowledgement packets are much more lkely to get lost. In addton, n case of short TTL, ntermedate nodes n QoS-ACA and S-W ARQ approaches wll stll relay expred packets towards the base staton whch comes n the expense of energy consumpton. VI. A HYBRID APPROACH Fgure 5 shows each of these three approaches outperforms the other two under some condtons. Therefore, t s more effcent to leverage the beneft from each n a hybrd approach to acheve maxmum performance n terms of ht rato. The dea behnd ths hybrd approach s to make a selecton among these three approaches by lookng at the TTL of the packet and lnk relablty nterval related to a gven chan. The performance of the hybrd approach s plotted n Fgure 7. One can see, ths ht rato graph nherts advantages of the assocated graphs of Fgure 5. Fgure 4. Ht rato vs. Packet deadlne for 0.1<LR<1(top,0.4<LR<1(mddle,0.7<LR<1 (bottom Copyrght (c IARIA, 2012. ISBN: 978-1-61208-207-3 266
SENSORCOMM 2012 : The Sxth Internatonal Conference on Sensor Technologes and Applcatons Fgure 5. Ht rato vs. Lnk relablty vs. Packet deadlne for READ (top QoS-ACA(mddle and S-W ARQ(bottom whle duty cycle of the left graphs s 0.99 and rght graphs s 0.1 Copyrght (c IARIA, 2012. ISBN: 978-1-61208-207-3 267
SENSORCOMM 2012 : The Sxth Internatonal Conference on Sensor Technologes and Applcatons Fgure 6. Comparson Between Total and Useful Energy Consumpton for READ (top QoS-ACA(mddle and S-W ARQ(bottom whle duty cycle of the left graphs s 0.99 and rght graphs s 0.1 Copyrght (c IARIA, 2012. ISBN: 978-1-61208-207-3 268
SENSORCOMM 2012 : The Sxth Internatonal Conference on Sensor Technologes and Applcatons Fgure 7. Ht rato vs. Lnk relablty vs. Packet deadlne for Hybrd approach whle duty cycle of the left graphs s 0.99 and rght graphs s 0.1 VII. CONCLUSION AND FUTURE WORK In ths paper, we propose READ, a relable and real-tme aggregaton-aware data dssemnaton protocol desgns for long chan-type wreless sensor networks, to cope wth the problem of effcent data gatherng of delay constraned sensor data. Long lnear chan-type sensor networks have often a large number of hop counts and to operate for a long tme, they usually need to work on a low duty cycle. We nvestgate the relatvely unexplored relatonshp between TTL and lnk relablty wth the attaned ht rato for tmecrtcal WSNs. READ allocates avalable packet s TTL proportonately to the packet loss probablty of the lnks along the forwardng path n order to udcously and farly use the packet s TTL on ntermedate nodes n such a way that relablty gan and on-tme end to end delvery rato s maxmzed. READ assumes the packet loss of each lnk s fxed for each smulaton and therefore does not update the packet loss of the lnks dynamcally based on the last status of the lnks. Ths s due to that fact that n ths paper we focus on fndng the relatonshp between TTL and lnk relablty wth the attaned ht rato. In our ongong work, we enhance READ by consderng dynamc changes of lnks relablty and wll modfy READ n such a way to be able to adaptvely change number of copes each node s allowed to send based on the last status of the lnk relabltes. We also consder comparng READ wth forward error correcton mechansms n on future work to know how well READ functons. REFERENCE [1] Dezfoul B., Rad M., Nematbakhsh M., and Abd Razak S.,: A Medum Access Control Protocol wth Adaptve Parent Selecton Mechansm for Large-Scale Sensor Networks. In IEEE 24th Internatonal Conference on Advanced Informaton Networkng and Applcatons, pp 402-408ngapore (2011. [2] Taghkhak, Z., Meratna, N., Zhang, Y., and Havnga, P.: QoS-aware Chan-based aggregaton n cooperatng VCN and WSN. In the book of Roadsde Networks for Vehcular Communcatons: Archtectures, Applcatons and Test Felds, In press (2012. [3] He, T.tankovc, J., Lu, C., and Abdelzaher, T.: SPEED: A stateless protocol for real-tme communcaton n sensor networks. In 23 rd Internatonal Conference on Dstrbuted Computng Systems, pp. 46-55, RI (2003. [4] Felemban, E., Lee, C., Ekc, E., Boder, R., and Vural.: Probablstc QoS guarantee n relablty and tmelness domans n WSN. In INFOCOM, pp 2646-2657(2005. [5] Km, K., Park., Park H., and Ham, Y.: Relable and real-tme data dssemnaton n wreless sensor networks. In IEEE Mltary Communcaton. pp 1-5an Dego (2008. [6] Soyturk, M., Altlar, D.: Relable real-tme data acquston for rapdly deployable msson-crtcal Wreless Sensor Networks. In IEEE INFOCOM, pp 1-6, Phoenx (2008. [7] Lndsey., Raghavendra, C.S.: PEGASIS: Power-effcent gatherng n sensor nformaton systems. In IEEE Aerospace Conference, pp 1125-1130, Montana (2002. [8] J. Walrand, Communcaton Networks: A Frst Course. Boston, MA: Irwn and Aksen, (1991. [9] F. Halsall, Data Communcatons, Computer Networks and Open Systems. U.K.: Addson-Wesley, (1996. [10] M. Schwartz, Telecommuncaton Networks: Protocols, Modelng and Analyss. CA: Addson-Wesley, (1987. VIII. ACKNOWLEDGEMENT Ths work s supported by IST FP7 STREP GENESI: Green sensor NEtworks for Structural monitorng proect. Copyrght (c IARIA, 2012. ISBN: 978-1-61208-207-3 269