Fault Tolerant Routing For Wireless Sensor Grid Networks

Transcription

1 Fault oleant Routng Fo Weless Senso Gd etwoks Xn-ng Huang, Jng Deng 2, Jng a and Zeyu Wu Depatment of Electcal Engneeng 2 Depatment of Compute Scence Unvesty of ew Oleans, ew Oleans, A 7048, USA Abstact Weless senso netwoks technology povdes an oppotunty fo nnovaton. It also bngs unque challenges. Fault toleant outng s a ctcal task fo senso netwoks opeatng n dynamc envonments. In ths pape, we pesent an expemental study on fault toleant outng fo weless senso gd netwoks. A netwok may be sepaated nto pattons owng to the boken ado lnks esulted fom the node falues. Snce the levelng algothm woks effectvely fo unpattoned netwok, a combned technque wth extended tansmsson ange s nvestgated to esolve the netwok pattonng poblem. he expemental esults show ths technque educes the pobablty of netwok pattonng sgnfcant. It also demonstates nea optmal netwok coveage and coveage effcency wth andom dead nodes dstbutons. Keywods weless senso netwoks, netwok coveage, fault toleant outng, levelng algothm I. IRODUCIO Weless senso netwoks epesent an emegng technology that has become vey appealng to eseaches. It s consdeed as a next geneaton technology to bdge between the Intenet and the physcal wold. In ecent yeas, many outng potocols have been successfully developed fo dffeent applcatons of weless senso netwoks. Dect dffuson s a -centc outng potocol that s developed fo nfomaton dssemnaton n senso netwoks []. owenegy adaptve clusteng heachy (EACH) s a wellknown cluste-based algothm [2]. Geedy pemete stateless outng (GPSR) s a geogaphc outng potocol [3]. A compason of many othe exstng potocols s avalable n [4]. ost of the above outng potocols wee focused on the effectve nfomaton eteval wth the emphass on enegy effcency fo senso netwok. In ths pape, we pesent an expemental study on fault toleant outng fo weless senso gd netwoks. evelng algothm s pesented as an enegy effcent appoach wth automatc outng path update fo unpattoned netwok. Extendng tansmsson ange s poposed fo effectve netwok coveage n pattoned netwok. hese two methods ae then combned to povde a obust, fault toleant outng scheme fo weless senso gd netwoks. he est of the pape s oganzed as follows: Secton 2 ntoduces the netwok topology of the applcaton-specfc weless senso gd, and then descbes the detals of the poposed fault toleant outng algothms. In Secton 3, we povde the pefomance analyss of the poposed fault toleant outng scheme. he expemental esults ae lsted n Secton4, followed by the concluson n Secton 5. II. FAU OERA ROUIG AGORIHS Weless senso netwoks have been appled n a vaety of ndustal, medcal, and mltay applcatons. A lage numbe of senso nodes can be dstbuted n vaous topologes. Fo secuty o envonmental sensng applcatons n uban aea, one of the most convenent deployments s to attach the senso nodes wth the oadway steetlghts. he senso nodes ae dstbuted along steets and avenues as n a geogaphc oad map. heefoe, the netwok becomes a gd, called weless senso gd netwoks. Fgue shows an example of weless senso gd netwok. We andomly pck a node to seve as the snk and assume that the pocessng cente s located at that node. Fo fault toleance study, sensos nodes ae andomly selected as dead nodes wth a cetan pobablty. Row 3 Row 2 Row Row 0 Column 0 Column Column 2 Column3 Pattoned netwok Senso node Dead node Snk Fg.. An example of the weless senso gd netwok In dynamc envonment of seno netwoks, some nodes can be faled due to a vaety of easons ncludng powe depleton, ccut malfuncton, pocesso falue, unelable ado lnks, and etc. he am of fault toleance outng s to mantan the effectve netwok coveage and undsupted nfomaton eteval fom the feld. In fault toleant outng, the absolute node coveage, as the pecentage of the lve nodes ove the total numbe of nodes, s less of the nteests.

2 It s moe mpotant to consde the actual netwok coveage and the coveage effcency. he defntons of these two paametes ae gven below: etwok coveage s defned as the total numbe of actve nodes ove the total numbe of nodes n the netwok. hee exsts at least one outng fom an actve node to the snk. n d netwok _ coveage () n Whee n s the total numbe of nodes, d s the numbe of dead nodes, and s the aveage numbe of nactve nodes n the netwok. Coveage effcency s defned as the numbe of actve nodes ove the numbe of lve node. If thee s no outng path fom a lve node to the snk, the lve node s consdeed nactve. n d cov eage _ effcency (2) n d A. evelng algothm fo unpattoned netwok evelng algothm s poposed as an effectve, lowcomplexty outng technque fo unpattoned netwok. In ths algothm, each node s assgned wth a level value that ndcates the dstance hops to the snk. Dung the ntal setup phase, the level values of all nodes ae set as nfnty. he snk fst ntates a RREQ message to ts neghbo and ndcates a level value of zeo. he neghbo nodes ecevng ths message change the level value to and send the RREP message. he same pocedue quckly popagates though the ente netwok, smla to the ntal oute dscovey as n AODV [6]. he pocess s natually analog to the wate flowng fom the hgh elevaton to lowe level, thus we called t the levelng algothm. When some nodes become dead n the netwok, the level algothm s able to automatcally update the outng paths by changng the level values. he detal pocedue fo the adaptve levelng outng algothm s lsted below:. Set the level value of the dead nodes to nfnty. 2. Fo any gven node wth level m, thee exsts at least one neghbo node whose level value s m- (except fo the base staton wth zeo value). Suppose the smallest level value of all neghbos s n. If n m, the cuent node value emans; If n < m, the cuent node value s set as n+; If n > m-, the cuent node level s set to nfnty. 3. he same ule above s appled to evey node epettvely untl the netwok conveges. he convegence tme and the oute mantenance ovehead ae detemned by the as well as the locatons n the netwok. Howeve, the levelng algothm s lmted to the unpattoned netwoks. A pattoned netwok mples a cetan aea of the netwok that contans one o moe lve nodes but has no connecton to the outsde of the aea as llustated n Fgue. When the levelng algothm conveges, the level values of all these solated nodes tun nto nfnty that mples no vald path s avalable fom the node to the snk. It s mpeatve to develop an mpoved algothm that can ovecome such scenao. B. Extendng ange method A heustc appoach to solve the pattoned netwok poblem s to ncease the tansmsson powe and to extend the communcaton ange of the nodes as needed. As n the weless senso gd netwok showed n Fgue, a lve node wth level value m should have one o moe next hop node located as the mmedate neghbo wth the level of m-. If a node detects that thee s no next hop node avalable due to node falue, a staghtfowad appoach s to ncease ts tansmsson powe to extend the communcaton ange. Due to the concen of enegy consumpton, the powe ncement s lmted to fou tmes of the mnmum tansmsson powe n ths pape that esult n a doubled communcaton ange accodng to the path loss model [2]. Equvalently, t povdes the addtonal ablty fo the actve nodes to skp any sngle dead node along the outng path. In pactce, we allow a node to extend ts tansmsson ange mmedately upon detectng the dead next hop node. Snce the outng paths n the netwok lagely eman ntact, the oute mantenance ovehead s low. Howeve, the extendng ange method has the dsadvantage of exhaustve enegy consumpton, and s lack of outng flexblty. It smply extends the communcaton ange of affected nodes, but does not pefom oute dscovey to update the outng table of othe nodes n the netwoks. heefoe, t does not guaantee that all physcally eachable nodes can be outed to the snk though the actve outng paths fo a pattoned netwok. C. he combned technque We consde a combnaton of the above two methods n ths secton. he oute mantenance pocedue s ntated fom the snk wth a zeo level value. If thee s no next hop avalable among the dectly connected neghbo nodes, ange extenson s equested. Consequently, local outng path update s pefomed mmedately afte each ange extenson. hese two pocedues ae executed altenatvely whle the outng path mantenance popagates though the ente netwoks. Fo valdaton pupose, the same pocess s epeated and the node level value s updated f a shote path s avalable. It s woth to menton that the combned technque s a geedy algothm that conveges quckly. It guaantees that all eachable nodes wll be connected upon completon of the algothm. Howeve, the updated outng path does not necessaly eflect the lowest powe consumpton and mnmum numbe of hops fom each node to the snk.

3 III. AAYSIS We analyze the poposed scheme n ths secton. Fst, the followng denotatons ae used thoughout ou analyss: : total numbe of wokng sensos; : total numbe of levels n the netwoks; : the level of senso, assumng the snk has the level value of 0; : the numbe of nodes at level ; S : numbe of bts of nfomaton geneated by each wokng senso pe samplng tme peod. All these nfomaton need to be tansmtted towad the snk. Data aggegaton may take place; O : numbe of bts of a heade; S max : maxmum payload length of a. Geneally, S max > S c : compesson ato due to fuson. hs s the ato of aggegatng smla esults nto a moe compact. c < ; t : tansfe ate fo evey node n the netwok (bts/sec) o : total tansmsson ovehead n bts; f : total taffc n the netwok pe unt tme; Assumng each senso caes out the same amount of sensng tasks, evey node geneates the same ate. he total payload of the netwok s *S. In the fully-connected netwok appoach, whee each wokng senso sends towads the snk dectly. Snce each node sends a to the snk, the total tansmsson ovehead s, O o (3) he total taffc of the fully-connected netwok s, f ( S + O ) (4) he total tansfeng tme s, tans ( S + O) t (5) Usng the levelng algothm, the total tansmsson ovehead s the same as O, wthout consdeng the maxmum payload length of a. It s assumed that evey node only tansmts once n each acquston tme peod. he total taffc s, ( ) f Sc + O Fo a senso at level, he payload S s compessed (- ) tmes along the path to the snk. he fst-level does not pefom compesson, because thee s no aggegaton. Fo the levelng method, the tansfe tme s detemned by the numbe of levels, the nfomaton geneaton ate at evey senso node S, and the numbe of nodes on each level, whee (6) (7) Assumng unfom netwok dstbuton, the total tansfeed n the netwok s, f S c whee c s compesson ato due to aggegaton. o aggegaton occus at oute level. he aveage tansmsson ate fo a node at level s, S c Gven the maxmum payload length S max, the numbe of s pe node at level s, S Smax c (8) (9) (0) Fo unfom senso netwok, the total numbe of s tansfeed n the netwok s, S c Smax he total tansmsson ovehead s, o () O (2) he total tansfe tme s tans IV. S c + t O EXPERIEA RESUS (3) he expemental setup of the weless senso gd netwok s shown as n Fgue, wth 4 ows and 4 columns and a total of 2 senso nodes. he case wth a sngle snk s consdeed and the locaton of the snk s andomly selected. he tansmsson dstance fo the levelng algothm s one hop, and the extendng ange s up to two hops. he smulaton code fo all thee algothms s developed n atlab. Fo each algothm, the expemental esults ae obtaned by vayng the n the netwok. he locatons of the dead nodes ae andomly selected. Each case has been smulated wth a total of 0 7 teatons.

4 Pobablty of netwok pattonng levelng algothm extendng ange combned technque coveage effcency levelng algothm combned technque dea case Fg. 2. Pobablty of netwok pattonng Fgue 2 shows the pobablty of pattoned netwok nceases as the gows fo all thee algothms. Result of the levelng algothm shows the pobablty of pattoned netwok eaches 99% wth only 2 dead nodes. Whle the extendng ange method educes the pobablty, the combned technque s a sgnfcantly bette appoach to avod netwok pattonng (b) Fg. 3. Pefomance compasons (a) netwok coveage compason (b) coveage effcency compason Fgue 3 shows that the combned technque can acheve bette pefomance than the levelng algothm n fault toleant outng. Known the numbe of actve nodes and the locatons, the deal netwok coveage and coveage effcency can be computed. Result of the combned technque s appoachng the dea case. netwok coveage levelng algothm combned technque deal case (a) V. COCUSIO hs pape pesents an expemental study on fault toleant outng algothms fo weless senso gd netwoks. Fst, levelng algothm s poposed as an enegy effcent method fo oute dscovey and mantenance. Secondly, extendng the tansmsson ange method s pesented to ovecome lmted pefomance of the levelng algothm on pattoned netwok owng to the dead node. astly, a combnaton of these two technques s nvestgated to educe the pobablty of netwok pattonng. he smulaton esults show that the combned technque sgnfcantly mpoves the communcaton n pattoned netwoks. It povdes s bette pefomance n netwok coveage and coveage effcency as well. Fo futue wok, the balance of node enegy consumpton wll be nvestgated fo the poposed technques. he extenson fo multple snks wll also be studed. ACKOEDGEE hs wok s suppoted n pat by the ASA EPScoR pogam unde eseach gant ASA/EQSF (2005)-DAR-

5 9 and the ousana State Boad of Regents Industal ed Reseach Subpogam (IRS) unde gant EQSF-( )- RD-B-. he authos ae also vey gateful to the anonymous evewes fo the nstuctve suggestons that led to an mpoved qualty of ths pape. REFERECES [] C. Intanagonwwat, R. Govndan, and D. Estn, Dect dffuson: a scalable and obust communcaton paadgm fo senso netwoks, n Poceedngs of obcom, August, [2] W. Henzelman, A. Chandakasan, and H. Balakshnan, An applcaton-specfc potocol achtectue fo weless mcosenso netwoks, IEEE ansactons on Weless Communcatons, vol., no. 4, pp , Octobe [3] B. Kap and H.. Kung, GPSR: geedy pemete stateless outng fo weless netwoks, n Poceedngs of the obcom, August, [4] A. Ahmed, H. Sh and Y. Shang, A suvey on netwok potocols fo weless senso netwoks, n Poceedngs of the Intenatonal Confeence on Infomaton echnology, pp , August, [5] Y. Xue and K. ahstedt, Fault oleant Routng n oble Ad Hoc etwoks, In Poceedngs of IEEE Weless Communcaton and etwokng Confeence, pp , ach, [6] E. Roye and C. oh, A evew of cuent outng potocols fo ad-hoc moble weless netwoks, IEEE Pesonal Communcatons agazne, pp , 999.