CHAPTER-5 PROBABILISTIC MODEL FOR RELIABILITY ANALYSIS IN WIRELESS SENSOR NETWORKS

Transcription

1 PROBBILISTIC MODEL FOR RELIBILITY NLYSIS IN WIRELESS SENSOR NETWORS CHPTER-5 PROBBILISTIC MODEL FOR RELIBILITY NLYSIS IN WIRELESS SENSOR NETWORS dancmn in wirlss snsor nwors chnology nabls a wid rang of applicaions such as halh car, indusrial auomaion, ambin condiions monioring and scuriy and dfns sysms. WSNs dsignrs ar facing many challngs in ming applicaion rquirmns.g. rliabiliy, faul olranc, lifim, hroughpu and rsponsinss c as applicaion rquirmns and nironmnal condiions chang or im. Failur of WSN may rsul caasrophic consquncs li loss of lif in h cas of halh car applicaion and major disasrs in h cas of dfns sysms. This chapr prsns a probabilisic modl basd on Maro modling for rliabiliy analysis by adding rdundancy wihin a snsor nod o rplac h fauly snsors in cas failur occurs. Th basic ida in his chapr is o addrss and analyz h rliabiliy issus o dic a rliabl and faul olran modl for a snsor nwor sysm. W analyzd h modl in rms of rliabiliy and MTTF Man-Tim-To-Failur. Rs of h chapr is organizd as follows: Scion 5. prsns h inroducion followd by h bacground in Scion 5.. y issus bhind h wor ha bn prsnd in Scion 5.. In Scion 5., a brif dscripion of rminology of rliabiliy and faul olranc has bn prsnd. nalysis of sysm modl has bn prsnd in Scion 5.5. Rsuls ha bn gin in Scion 5.6 followd by h conclusion in Scion 5.7. Finally, chapr has bn summarizd in Scion INTRODUCTION Wirlss Snsor Nwor is a group of spaially disribud snsors o monior h physical or nironmnal condiions so ha daa can b ransfrrd from h sourc o h dsinaion. Though Wirlss Snsor Nwors wr iniially moiad by h dfns applicaions bu nowadays hy ha bn h prfrrd choic for h dsign and dploymn of nx gnraion monioring and conrol sysms [9, ].Th WSN is buildup of hundrds and housands of nods whr ach nod is conncd o snsors. Small siz and low cos of h nods ma hm araci for widsprad dploymn and also causs a disadanag of low-opraional 76

2 PROBBILISTIC MODEL FOR RELIBILITY NLYSIS IN WIRELESS SENSOR NETWORS rliabiliy. Somims du o h failur of som of is nods, h snsor nwor communicaion fails. Snsor nods can fail, du o numbr of facs, such as xposur o harsh nironmns or simply nrgy dplion, and influnc WSN dpndabiliy [].In ordr o fac his problm, and xploring h fac ha WSN us sral nods, sral faul olranc masurs proposd in h liraur rly on h inhrn nod rdundancy []. Indd, h abo mniond ida o xplor h naural rdundancy proidd by h gra numbr of nods ha in gnral compos a WSN proids good rsuls. Nighbor nods can monior ach ohrs bhaiors and whn a problm is dcd, such as a siuaion in which a nod is prmannly ou of ordr, on or som of is nighbors can assum h ass ha wr priously xcud by h fauly nod []. Howr, h assumpion of accss o rdundan nods is a ncssary condiion for h succss of his approach. uhor in [9], proposd an algorihm ha allows o dc whn h connciiy o a spcially dsignad nod has bn los. uhors in [] has shown h daild sudy on h facors affcing h rliabiliy in WSNs. Som of h major facors affcing h rliabiliy in WSNs ar Hardwar failur, inappropria communicaion schm, consraind rsourcs in snsor nods and rror pron wirlss communicaion mdium. 5. BCGROUND Th Nod failur is xpcd o b qui common in WSN, du o limid nrgy rsourc and nironmnal dgradaion. This scnario is mosly ru for h snsor nwors ha ar dployd in harsh and dangrous nironmns for applicaions such as fors fir monioring. Whn a numbr of snsors fail for whar may b h rason h rsuling nwor opology may b disconncd and which may rsul as a failur of s of nods. Th nods ha ha no faild bcom disconncd from h rs of h nwor. Rliabiliy and faul olranc ar closly rlad wih ach ohr and hnc rliabiliy of any sysm can b nhancd by incrasing h faul olranc of h sysm. In WSNs, faul olranc can b incrasd by adding hardwar/ sofwar rdundancy in h nwor. Rdundancy may b addd wihin a WSN, wihin a clusr or wihin a snsor nod o achi h faul olranc. In his wor, w ha proposd a rliabl WSN modl by adding h rdundancy wihin a snsor nod as snsors ha highr ras of failur han ohr componns procssors, ranscirs c., moror, snsors ar chapr han ohr componns, adding addiionalspar snsors conribu lil o a snsor nod s cos. In his wor, a Maro modl has bn proposd 77

3 PROBBILISTIC MODEL FOR RELIBILITY NLYSIS IN WIRELESS SENSOR NETWORS for characrizing rliabiliy and Man Tim To Failur MTTF as i proids an insigh ino h yp of snsor nods fasibl o m h applicaion s rquirmn and may also b hlpful for h dsignr of WSN in drmining h xac numbr of snsor nods o m h rliabiliy rquirmn of h applicaion. 5. ISSUES Rliabiliy is on of h mos imporan issus in any nwor. Rliabiliy is of prim concrn in h nrgy consraind nwors such as wirlss nwor. s rliabiliy is srly affcd by rrors and fauls ha occur du o many rasons such as Hardwar malfuncioning, bugs in sofwar, nironmnal hazards c. Thus a snsor nwor should b rliabl nough o dal wih such rronous condiions ffcily. In ordr o achi a br rliabiliy of h sysm, on soluion is o impro h qualiy of spars; anohr on is o incras h numbr of spars. W considr in our modl ho or sand-by spars, which mans ha hy rplac immdialy h faild snsor hr is no gap in im bwn h momn h snsor has faild and h momn spars rplac i. Whn h spars subsiu a modul, hn i has h sam failur ra as h modul. 5. RELIBILITY ND FULT TOLERNCE Rliabiliy is dfind as h probabiliy of propr funcioning of any sysm. Whn a sysm dos no m is spcificaion, a failur is prsumd. Sysm rliabiliy may dgrad du o many rasons such as hardwar failur incorrc opraion of sysm componns, noisy communicaion channl affcing inpus, inappropria and in accura dsign considraions o m h rquirmns and of cours changs in h nironmn du o suddn changs in nironmnal facors. Th faul olranc is abiliy for a sysm o coninu funcioning proprly n afr failurs in any par of h sysm ha occurrd. Faul olranc in wirlss snsor nwor can b proidd in hr ways []: a. Through hardwar impromn and bacup componns, b. Through raffic managmn and c. Through rdundan nwor dsign. 78

4 PROBBILISTIC MODEL FOR RELIBILITY NLYSIS IN WIRELESS SENSOR NETWORS Wirlss Snsor Nwor WSN is ransforming ino a muli sric mdium lading o h conrgnc of oic, ido and daa communicaion. Each yp of sric has a paricular consrain and i has o b saisfid for h communicaion o b ffci. In [5] an inrsing rsarch rgarding h faul olranc aspcs of a snsor nwor assums ha h nods ar ihr aci or inaci wih Brnoulli modl. In cas ha on or mor snsor fails, ohr snsors of a diffrn yp can subsiu hir wor, such ha h faul gos. Rliabiliy: Th probabiliy ha a componn suris unil somim is calld h rliabiliy R of h componn. L X b h random ariabl rprsning h lif im of a componn hn RPX>-F; whr F is calld h unrliabiliy of h componn. Th unrliabiliy of a sysm is F - R. For any sysm, Iniially h sysm is funcional a : R, F. Enually h sysm will fail a T, RT, FT. 5.5 SYSTEM MODEL Considr a WSN consising of wo diffrn ind of snsor nods rprsnd wih and. Th snsor which is ou of ordr can b rplacd by rspci spars S and S. Thy ar considrd as ho spars o rplac h faild snsor immdialy wihou dlay. Failur ra of h rplacd snsor has bn considrd h sam as spcifid for h rplacd on. For br rliabiliy of h WSN, ihr w ha o impro h qualiy of indiidual snsors or should incras h numbr of addiional rdundan snsors spars o rplac h fauly snsors. Sinc h failur of nwor is no crain, h bhaior of h modl has bn considrd as a Maro Chain wih absorbing sa. Bhaior of h proposd modl has bn dscribd as undr: Maro Chain for WSN wih wo yps of Snsor Nods and on Spar Snsor of ach yp Bhaior of his yp of WSN has bn shown in Figur as a discr paramr Maro Chain wih snsors of ind and of ind along wih on spar snsor for ach ind. For simpliciy, h failur ra of ach snsor has bn considrd as sam, i.. S. For h Maro Chain rprsnd by h sa spac {,,,, } S shown in figur, h probabiliy disribuion cor a im can b gin as: 79

5 PROBBILISTIC MODEL FOR RELIBILITY NLYSIS IN WIRELESS SENSOR NETWORS 8 ],,,, [ i Figur 5.: Maro Chain for WSN wih wo inds of snsor nods and on spar snsor for ach ind Tabl 5.: Sa Spac rprsnaion of Maro Chain shown in Figur 5.. Sa of sysm Dscripion of sasfuncional Snsors S S S S FILED FILED Bhaior of Maro chain shown in Figur can b dscribd by h sochasic marix gin as:- S S S S P ii Soling i and ii:

6 PROBBILISTIC MODEL FOR RELIBILITY NLYSIS IN WIRELESS SENSOR NETWORS 8 d d d d d d d d d d iii From h gin boundary condiions,,,,. Soling quaion in iii, Th probabiliy ha h sysm will ma a jump o h faild sa is gin by. i and hnc h rliabiliy will b - R... Considring, h man im o failur will b MTTF i Similarly h rliabiliy xprssion for h WSN wih snsors of ind and snsors of ind along wih wo spars of ach ind can b drid as R n ii

7 PROBBILISTIC MODEL FOR RELIBILITY NLYSIS IN WIRELESS SENSOR NETWORS MTTF iii 5.6 RESULTS Thorical analysis of h sysm modl has bn shown graphically considring a singl snsor nod of yp and mulipl snsors of yp wih h assumpion ha h failur ra of all nods as a ach, sconds. Figur 5.: MTTF wih on spar snsor Figur 5.: MTTF wih wo spar snsors

8 PROBBILISTIC MODEL FOR RELIBILITY NLYSIS IN WIRELESS SENSOR NETWORS Figur 5.: Comparai sudy of MTTF wih on/wo spar snsors Figur 5., 5. shows h MTTF wih on and wo spar snsors of ach yp rspcily. Boh figur shows ha MTTF dcrass wih h incrass in aci snsor nods. Figur 5. shows h comparai sudy of h MTTF bwn h nwors wih on and wo spars of ach yp. I is concludd ha MTTF incrass wih h incras in spar snsors of ach yp. 5.7 CONCLUSION Woring Maro modl prod o b suiabl for h rliabiliy modling in WSNs du o h sochasic bhaior of h nwor failurs. For br rliabiliy, dsignr should ihr go for h improd qualiy of snsor nods or should incras h numbr of spar snsors o rplac h fauly on. nalysis shows ha h rliabiliy of WSN dgrads wih h incras in aci snsor nods in h nwor. 5.8 SUMMRY This chapr is a conribuing ffor o xplor h rliabiliy issus in WSNs. Rliabiliy has bn analyzd for h wo cass: wih on spar snsor, wih wo spar snsors. Rsuls show ha MTTF incrass wih h incras in spar snsors of ach yp. In h nx chapr, -Tir nural nwor basd modl has bn prsnd for rliabl and faul olran ransporaion of informaion dspi of h fac ha wirlss communicaion mdium is noisy and informaion may b corrupd during ransmission. 8