FPAR: Frequency and Power Attentive Routing Protocol for Impediment Lenient Mobile Sensor Networks

Transcription

1 Internatonal Journal of Scentfc and Research Publcatons, Volume 2, Issue 12, December FPAR: Frequency and Power Attentve Routng Protocol for Impedment Lenent oble Sensor Networks L. Chandra Shekar *,.L.Ravchandra ** *.Tech at Dept of ECE, Netaj nsttute of engneerng and technology, Hyderabad, AP, Inda ** Assocate Professor & HOD, Dept of ECE, Netaj nsttute of engneerng and technology, Hyderabad, AP, Inda Abstract- Impedment lenent oble Sensor Networks (ILSN) s a class of promsng networks that experence frequent and long-duraton parttons. Evaluate wth the conventonal networks, the dstnct characterstc s that there s no end-to-end connectvty between source and destnaton. The network topology may modfy dynamcally and arbtrarly. Ths characterstc and non-exstence of an end-to-end path poses a number of challenges n routng n ILSNs. So, Utlzng multreplca schemes to develop the routng performance s reasonable. ost of the presented mult-replca approach dstrbutes many copes of the messages nto the network for ncreasng the packet delvery rate. Ths operaton consumes a great amount of constraned resource of ILSNs. To solve ths problem we suggest a Rado Frequency and Power-Attentve Routng protocol (FPAR), whch cut down the replcas based on the Rado Frequency between the sensor nodes and snk node and the resdual Power of the sensor node. The packet delvery probablty s based on snk meetng frequency and nodes movement drecton. Then we develop our protocol by usng dverse targets called Dverse Targets Rado Frequency and Power Attentve Routng protocol (DTFPAR). Smulaton results ndcate that our proposed protocol acheves hgher message delvery ratos wth lower transmsson overhead and data delvery delay than exstng ILSNs routng protocols. Index Terms- Impedment Lenent moble sensor networks Routng protocols Dverse Targets I I. INTRODUCTION n recent years, many routng protocols have proposed for wreless sensor networks (WSNs). Tradtonal methods of routng are sutable for many sensor applcatons, but they cannot be appled to the scenaros wth ntermttent and low connectons because of sparse network densty, sensor nodes moblty and Power lmtaton. Two practcal examples of ths scenaro are pervasve ar qualty montorng and flu vrus trackng. In these examples for the most accurate and effcent measurement, wearable sensors that adapt to human actvtes has been bound. AS a result, the connecton between the moble sensors s poor and thus formng a well connected mesh network to transfer data through end-to-end connectons between sensor nodes and snks s dffcult. In order to deal wth ths problem, Impedment Lenent oble Sensor Networks (ILSNs) [1-5] has been ntroduced. ILSNs are the subset of the Impedment Lenent Networks (DTNs) [6-12] whch have many features such as node moblty, frequent and prolonged communcaton nterrupton between nodes, delay tolerance and resources lmtatons. A ILSN under our consderaton conssts of two types of nodes, the wearable sensor nodes and snk nodes. The former are attached to people (or other moble objects), collectng nformaton and formng a loosely connected moble sensor network for nformaton delvery. A number of hgh-end nodes (e.g. moble phones or personal dgtal assstants wth sensor nterfaces) whch servng as the snks to receve data from wearable sensors, are deployed at strategc locatons wth hgh vstng probablty or carred by a subset of people. One of the methods of data gatherng n ILSNs, are mult-replca schemes that generate manfold replcas for each message. Dstrbutng a message to a large number of nodes wll ncrease the probablty of packet delvery rate. For a ILSN that has lmted resources, duplcate messages wll ncrease traffc overhead, collson, delay and Power consumpton of moble nodes. In recent years, several mult-replca routng protocols [13-17] have been presented to ncrease the data delvery rate. These protocols can be dvded nto two categores: a) floodng-based approaches b) quota-based approaches. In floodng-based approaches, the nodes send copes of a message to all neghbor nodes, whle, n quota-based approaches, the nodes send fxed and lmted number of copes of a message and have better effcency than floodng-based approaches. In ths paper we have tred to present a replca adaptve routng protocol for ILSNs. The rest of the paper s organzed as follow: Secton 2 dscusses related work. Secton 3 presents the proposed protocol. Secton 4 dscusses proposed protocol wth mult snk. Secton 5 presents mtaton results. Fnally, Secton 6 concludes the paper. II. RELATED WORK There has been wde research on routng n ILSNs. The work dates back to before the term "delay-tolerant" was extensvely used. The adjectves "ntermttently-connected", "sparse" and "dsconnected" are also used to explan networks wthout constant end-to-end connectons. One of the categores of routng schemes s mult-replca methods. A majorty of exstng mult replca routng protocols, such as epdemc [13], are floodng-based. Epdemc protocol s attempts to gve all nodes a copy of every message, through random nteractons between nodes. If t s provded nfnte bandwdth and buffer resources, t could acheve a hgh data delvery rate and low data delvery delay. It has more overhead and Power consumpton that ncreases packet droppng and retransmsson. Dfferent from

2 Internatonal Journal of Scentfc and Research Publcatons, Volume 2, Issue 12, December floodng-based routngs, quota-based protocols such as Sprayand-Wat [17] and Spray-and-Focus [18] use fxed number of replcas. Spray-and-Wat "sprays" a number of copes nto the network and then "wats" untl one of these nodes meets the destnaton. Spray-and- Focus s very smlar to Spray-and-Wat. Ths scheme dstrbutes a small number of copes to a few nodes. Though, each relay node can forward ts copy further usng a sngle-copy utlty-based scheme, nstead of watng to delver t to the destnaton tself. Other endeavors amng to mprove the performance of ILSN routng nclude [19, 20]. In [19], a replcaton-based effcent data delvery (RED) protocol based on erasure codng technology s presented. RED conssts of two key components for data transmsson and message management. The frst makes decson on when and where to transmt data messages accordng to the delvery probablty. The second decdes the optmal erasure codng parameters based on ts current delvery probablty, n order to acheve the preferred data delvery rate whle mnmzng overhead at the same tme. Ths hstory-based method s not effectve and cannot denote the actual ablty that a node delvers data to snk nodes. In [20], the authors propose a essage Fault Tolerance-Based Adaptve Data Delvery Scheme (FAD) to ncrease the data delvery rate n ILSN. The FAD approach employs the message fault tolerance, whch ndcates the sgnfcance of the messages. The decsons on message transmsson and droppng are made based on fault tolerance for mnmzng transmsson overhead. The system parameters are cautously tuned on the bass of thorough analyses to optmze network performance. That protocol stll has a hgh overhead. Yong Feng et al. n [21] proposed a Dstance-Attentve Replca Adaptve Data Gatherng protocol (DRADG), whch uses a selfadaptng algorthm to cut down the number of redundant replcas of messages accordng to the sensor nodes' dstance and snk node and leverages the delvery probabltes of the moble sensors as man routng metrcs. Creatng message copes wthout consderng the sensor nodes' resdual Power maybe cause the faster sensor nodes' Power consumpton and t cause hole problem n the network and reduce the network lfe tme. III. RADIO FREQUENCY AND POWER ATTENTIVE ROUTING PROTOCOL (FPAR) As s descrbed above, FPAR dynamcally calculates the number of copes of each message based on two parameters: a) the Rado Frequency between the sensor node, that generates message and the snk nodes. b) Resdual Power of the sensor node. Resdual Power of sensor node consderaton n determnng number of replcas, reduce Power consumpton and prevent the creaton of holes n the network. Also, FPAR computes the delvery probablty of every moble node accordng to ts frequency of meetng wth the snk node and ts movement drecton. In ths secton, we wll explan the proposed protocol n detal. A. Network odel: We assume ntally all the N sensor nodes randomly deployed n a square area of A. All the sensor nodes are homogeneous. The maxmum transmsson range of all the sensor nodes s fxed to R. The moblty of all sensor node s assumed to follow the communty-based oblty model depcted n [22, 23] where the whole area s dvded nto several non-overlapped cells, one gatherng place (G) and communtes (C). Each sensor node has one home communty whch t s more lkely to vst than other communtes. Nodes randomly choose a destnaton and a speed and move there. Upon arrval at the destnaton, \the nodes pauses for a whle and then select a new destnaton. The destnatons are selected such that f a node s at home, there s a elevated probablty that t wll go to the gatherng place (but t s also for t to go to other places) and f t s away from home, t s extremely lkely that t wll return home. Each sensor node can compute ts locaton by GPS (Global Postonng System) [24-26]. The snk node s mmoble and t s located at G. ts locaton s known to all sensor nodes. B. essage Replca Number Calculaton: Accordng to the DRADG, replca number of each message calculated based on the dstance between the sensor nodes whch generates the message and snk node. In ths paper to ncrease the effcency of ths protocol, FPAR decdes the replca number of each message accordng to resdual Power of the sensor whch generates the message n addton ts Rado Frequency wth snk node. In the header of each message there s a feld of nteger type that holds the number of ts replca tcket. For example, when n generates a new message, value of d that s the current Rado Frequency between node n and the snk node equals: Where the locaton of node d ( x x ) ( y y ) 2 2 sn k sn k ( x, y ) n s ( x, y ) (1) and the locaton of snk node s sn k sn k The value of the tcket that denotes the upper bound of replca number defned as follow: d tcket a*( k * T * (1 a)* EN max Dmax ENmax (2) Where k and are constant parameters between 0 and 1; T max s the maxmum value of the tcket; D max s the Rado Frequency between farthest sensor node and the snk node n the network; EN s resdual Power of node n, EN max s the ntal Power of each node that t s equal for every sensor node. From Equaton 2, t can be found that the number of message replca s hgh n the node whch s closest to the snk and has the hghest level of remanng Power. Ths approach, decrease the message redundancy when sensor nodes and snk node are close to each other and the poor performance when they are far from each other. In addton, t cause Power effcency and avod problem of hole n the network.

3 Internatonal Journal of Scentfc and Research Publcatons, Volume 2, Issue 12, December C. Node Delvery Probablty Calculaton: In ths protocol, we establsh a probablstc metrc called delvery Probablty, p at every node. Ths parameter ndcates how ths node wll be able to drectly delver a message to the snk node. The calculaton of the delvery Probablty has several parts. Every sensor node calculates ts delvery probablty n accordance to ts frequency of meetng wth the snk node and ts movement drecton and sends the message to nodes wth hgh delvery probablty. The frst thng to do s to compute the meetng frequency of n n the most recent nterval of, denoted freq as by Equaton 3 as follows [21]: Where Num, s the meetng tme of node n wth the snk Num node n the latest nterval of, th s the threshold value that should be vared based on the applcaton. Then, we calculate F as follow: dst,sn k dst j,sn k F freq* dst,sn k (4) dst,sn k dst j,sn k Where and are the Rado Frequency between node and snk and node j and snk, respectvely. Num freq Numth Num Num, Num Num 1 th th (3) Fg. 1: Locaton of sensors on the way to target sensor The movement drecton of the sensor nodes s also mpressve n node delvery probablty. As shown n Fgure 1, f the sensor node moves towards the snk node, t s lkely to encounter snk node n a future perod of tme. We can calculate the packet delvery probablty, P as follow: P * F (1 )* P ( old ) (5) Here n Eq 5, the s weght parameter. Fnally, due to the node moblty, each node calculates the delvery probablty perodcally and broadcast the value to ts neghbors by hello messages. Forwardng Strateges: that updates t by recevng hello messages. When node n, has a message to forward, frst of all t looks up the node wth hghest delvery probablty n ts neghbor lst, denoted as n m. If P m s greater than P, then n m s next hop. Secondly, f the value of tcket s equal to 1 then n, drectly forwards to n m ; f else, tcket n, generates a replca of, denoted as ', set tcket tcket [ tcket [ /2], forwards ' to n m and fnally updates /2] and stores message nto ts routng queue. D. Queue anagement: In challengng networks lke ILSNs, manfold message replcas may be generated and buffered by dfferent sensors, resultng n redundancy. In order to acheve effectve data delvery rate and enhance network performance, queue management scheme s essental. The man dea of the queue management scheme s employng both survval tme and gvng more prorty to mportant message. E. essage's Survval Tme: We assume each data message has a feld that records ts survval tme. For example, the survval tme of massage m n the queue of sensor j, denoted as m n as as. When a message s generated,

4 Internatonal Journal of Scentfc and Research Publcatons, Volume 2, Issue 12, December ts endurance tme s ntalzed to be zero. When node j delveres a message m to sngle hop neghbor nodes, such as node n, the tme requred for transmsson be gnored and the node nserts the message to ts queue wthout any changes on amount of the survval tme. Therefore, the ntal value m j m n the same amount of before transmsson. If a source message has transmtted to ts next hop and t s nserted nto node's queue agan, ts survval tme s also unspecfed to be equal to the value before transmttng. Furthermore, for messages n the queue buffer, ther endurance tme should be updated wth the tme clock. F. assage's Prorty: Every sensor node mantans a lst of the messages n ts buffer that come from the followng sources: After the sensor nodes sense a data, t generates a message and nserts t nto ts data queue. (b) When a sensor node receves a message from other sensor nodes, t may nsert t to ts buffer. (c) After the sensor node sends the data message from ts buffer to other destnaton except the snk, f the message s generated by the source node tself, t may nsert the message agan, because there sn't any guarantee to delver the messages to the destnaton. essages n the frst classfcaton have hghest prorty and messages belongng to the second and thrd class are have mddle and the lowest prorty level respectvely. IV. IPLEENTATION OF QUEUE ANAGEENT SCHEE Implementaton of the queue management scheme s based on two parameters, the massage prorty and the data message survval tme. essages are sorted n the queue based on a descendng order of the prorty, f two messages have the same prorty level, then they are sorted based on ascendng order of survval tme, ndeed the massage that ts survval tme s less has a hgher prorty. The massage wll be dropped from the queue n the followng two occasons: a) the message survval tme exceeds the network's Impedment Lenent threshold (maxmum message delay value). b) When the queue s full and a new message arrves, ts precedence level s compared wth the prorty level of the message at the end of the queue and one wth less prorty level s dropped among them. Otherwse f the prorty levels are equal, then the one wth a longer survval tme s elmnated. Ths condton has been set to reduce Power consumpton, gven that the messages are delvered to the destnaton wth the hghest prorty or the massage be declared nvald. V. DIVERSE TARGETS RADIO FREQUENCY AND POWER ATTENTIVE ROUTING PROTOCOL (DTFPAR) Due to the battery resource constrants, savng Power s a crtcal ssue n ILSNs, partcularly n large ILSNs. One possble soluton s to deploy manfold snk nodes s smultaneously. Havng manfold snks n the network gves networks compared wth sngle snk sensor networks as follows: 1: They are more consstent because of the fact that nvaldaton of a snk node wll drag down the whole network n sngle snk networks. Generally there exsts a serous node Power bottleneck (around snks) f a sngle snk masses reports from too many sensors. They allevate the unbalanced Power consumpton. They suggest more adaptable functonal applcatons and communcaton cooperaton. In some applcatons, dfferent users (snks) may requre dfferent envronmental varables (temperature, humdty, lght ntensty, etc.) or data formats (mage, sound, vdeo, etc.). In ths tme, all nodes requre to cooperate wth each other durng the communcaton process. The work presented n ths secton s manly motvated by partly statonary, mult-snk deployments of ILSNs such as real-tme survellance and cty polluton montorng applcatons. ultple snks deployed n the network and each sensor node knows the locaton of all \the sensors. The sensor node that generates a data message, calculate Rado Frequency between tself and snk nodes accordng to Equaton 6 as follows: d x x y y For n 2 2 s ( ) ( ) 1... Where nodes. ds (6) s the Rado Frequency between n, and the snk Then t determnes number of hops towards every snk by Equaton 7: d x x y y For n 2 2 s ( ) ( ) 1... Where h s the hops between n and the snk nodes; r s the transmsson range of each node that s fxed. Every node chooses the snk that has mnmum hops to t as a management snk. Rest of the algorthm s lke the FPAR algorthm that s descrbed n secton 3. VI. EXPERIENTAL RESULTS We have smulated DTFPAR, EDRP[27], as well as epdemc[13] topologes usng XL and actonscrpt. The poston per hop transmsson dstance s 250m. For power mantenance functon, many smaller hop level nodes are taken. Power management s used n all three topologes, ncludng normal EPIDEIC topology, n whch a transmtter adjusts the transmsson power based on ts actual dstance to the next hop level recever. The network area n the smulaton s fxed to 1200(m) X 1200(m) and the nodes are arbtrarly dspersed n the network. The avalable transmsson power levels are 1; 5; 10; 15; 20; 25; 30; 35 mw. The Pm s set to 35 mw. The sesson arrval rate follows Posson dstrbuton and the sesson nterval follows Exponental allocaton. The applcaton topology s CBR (Constant Bt Rate) and the source and target pars are (7)

5 Internatonal Journal of Scentfc and Research Publcatons, Volume 2, Issue 12, December arbtrarly selected. The moblty follows customzed random waypont model [18] wth pause tme of thrty seconds. For each CBR sesson, 50 packets are sent for each second. The rate of route loss and collson are projected usng method descrbed n [12]. The detecton rate, whch can be descrbed as flter memory [11], s fxed to nearly 1. A smulaton result was ganed by averagng over 25 executons wth dssmlar seeds. We consder that there s no power savng approach for the nodes, and therefore, a node wll use power n montorng the channel even f t doesn t receve a packet. A node also utlzes power when overhearng packet transmssons. Therefore, the recevng power cannot be dynamcally controlled. In the smulatons, we thus dsregard the recevng power and focus only on the comparson of transmsson power. We frst evaluate the accuracy of the proposed cost model, we then study the performance of route detecton for each topology, and fnally we consder power utlzaton as well as RTS retransmssons n both statc and moble envronment. We compared the power utlzaton and the average number of RTS retransmssons of the DTFPAR, EDRP and basc EPIDEIC topologes by varyng the followng parameters: node count, average sze of the data transmsson packets, and advent rato of the connecton. The smulaton tme for each topology s 5 hours. We montored the total power utlzaton of all the packets delvered at target node, the count of delvered packets at target nodes, and the count of retransmssons RTS requred for each executon of the smulaton. The couple of evaluaton metrcs that used to evaluate the topologes are: Power Utlzaton per Packet: It s defned by the total power utlzaton dvded by the total number of packets delvered. Ths metrc ndcates the power effcency for each topology. Average RTS Retransmssons requred for each Data Packet: It s defned by the total number of RTS retransmssons dvded by the total number of packets delvered. The RTS packet s transmtted at the utmost power usage level and the packet sze s very lttle. The majorty of RTS retransmssons are due to collsons, together wth the collsons of both RTS messages and data packets. Hence, ths metrc can ndcate the pace of the collson for each topology. Hgher collson rate wll cause more power utlzaton, hgher end-to-end delay, and lower throughput. The smulaton results are shown n Fgure. 2 and 3. Accordng to these results, DTFPAR topology performs the best n terms of Power Utlzaton per Packet as well as Average RTS Retransmsson per Data Packet, followed by EDRP topology and EPIDEIC. Fg 2: Power Utlzaton rato between DTFPAR, EDRP and EPIDEIC

6 Internatonal Journal of Scentfc and Research Publcatons, Volume 2, Issue 12, December Fg 3: RTX and ReTX packets usage Rato comparson between EPIDEIC, EDRP and DTFPAR VII. CONCLUSION Ths paper deals wth effcent data transmsson n the Delay- Tolerant oble Sensor Network (ILSN).By takng nto consderaton the unque characterstcs of ILSN, such as sensor node moblty, loose connectvty and delay tolerablty, whch dstngush ILSN from conventonal sensor networks, we have proposed a new routng approach called A Rado Frequency and Power Attentve Routng Protocol (FPAR) for ILSN. In FPAR, replca number of each message calculated based on the resdual Power of the sensor nodes whch generates the message and ts Rado Frequency and snk node. FPAR makes routng decsons accordng to delvery probablty. The expermental results show that our proposed FPAR protocol provde better performance at the cost of lower traffc overhead and Power consumpton and hgher delvery rate than exstng protocols. Furthermore, we mprove FPAR by usng Dverse Targets called DTFPAR, the smulaton results show that wth more snk nodes present, we have a hgher delvery rate and lower delvery delay. REFERENCES [1] Lu, N.B.,. Lu, J.Q. Zhu and H.G. Gong, A Communty-Based Event Delvery Protocol n Publsh/Subscrbe Systems for Impedment Lenent Sensor Networks. Sensors, 9: [2] Song, G.., Y.X. Zhou, F. Dng and A.G. Song, A oble Sensor Network System for ontorng of Unfrendly Envronments. Sensors, 8: [3] Wang, Y., F. Ln and H. Wu, Effcent Data Transmsson n Delay Fault Tolerant oble Sensor Networks (DFT-SN). In Proceedngs of IEEE Internatonal Conference on Network Protocols (ICNP 05), Boston, A, USA, [4] cdonald, P., D. Geraghty, I. Humphreys, S. Farrell and V. Cahll, Sensor Network wth Delay Tolerance (SeNDT). In Proceedngs of 16 th Internatonal Conference on 2006 Computer Communcatons and Networks, ICCCN 2007, Dubln, Ireland, [5] anwarng, A., J. Polastre, R. Szewczyk, D. Culler and J. Anderson, Wreless Sensor Networks for Habtat ontorng. In Proceedngs of AC Internatonal Workshop on Wreless Sensor Networks and Applcatons (WSNA). Atlanta, GA, USA, [6] Fall, K., A Delay-Tolerant Network Archtecture for Challenged Internets. In Proceedngs of AC SIGCO 2003 Conference on Computer Communcatons, Karlsruhe, Germany, [7] Burlegh, S., A. Hooke, L. Torgerson, K. Fall, V. Cerf, B. Durst, K. Scott and H. Wess, Delay-Tolerant Networkng-An Approach to InterplanetaryInternet. IEEE Communcatons agazne,41: [8] Leguay, J., T. Fredman and V. Conan, 2005.DTN Routng n a oblty Pattern Space. In Proceedngs of AC SIGCO 05 Workshop onimpedment Lenent Networkng and Related Topcs. Phladelpha, PA, USA, [9] Camp, T., J. Boleng and V. Daves, A Survey ofoblty odels for ad hoc Network Research. Wreless Communcaton & oble Computng (WCC), 2: [10] Warthman, F., Delay-Tolerant Networks (DTNs); DTN Research Group: arch Avalable onlne: pnsg. org/reports/ DTN_Tutoral11.pdf/ (accessed on 25 July 2010). [11] Neely,.J. and E. odano, Capacty and Delay Tradeoffs for adhoc oble Networks. IEEE Transactons on Informaton Theory, 51: [12] Partan, J., J. Kurose and B. Levne, A Survey of Practcal Issues n Underwater Networks. In Proceedngs of the 1st AC Internatonal Workshop on Underwater Networks, Los Angeles, CA, USA, pp: [13] Vahdat, A. and D. Becker, Epdemc Routng for Partally Connected ad hoc Networks; Techncal Report CS ; Duke Unversty: Durham, NC, USA, [14] Burgess, J., B. Gallagher, D. Jensen and B.N. Levne, axprop: Routng for Vehcle-Based Dsrupton-Tolerant Networks. In Proceedngs of IEEE INFOCO, Barcelona, Catalunya, Span, [15] Ramanathan, R., R. Hansen, P. Basu, R. Han and R. Krshnan, Prortzed Epdemc Routng for Opportunstc Networks. In Proceedngs of AC obopp 07, San Juan, PR, USA, [16] Balasubramanan, A. and B.N. Levne, Venkataraman, A. DTN Routng as a Resource Allocaton Problem. In Proceedngs of AC SIGCO, Kyoto, Japan, pp: [17] Spyropoulos, T., K. Psouns and C. Raghavendra, Spray and Wat: An Effcent Routng Scheme for Intermttently Connected oble Networks. In Proceedngs of AC SIGCO Workshop on Delay- Tolerant Networkng, Phladelpha, PA, USA, 26 August [18] Spyropoulos, T., K. Psouns and C.S. Raghavendra, Spray and focus: Effcent oblty-asssted Routng for Heterogeneous and Correlated

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