![無線傳感器網(wǎng)絡(luò)能量優(yōu)化設(shè)計_第1頁](http://file4.renrendoc.com/view10/M02/08/38/wKhkGWV6uESAOJXOAALtpmOJZqE515.jpg)
![無線傳感器網(wǎng)絡(luò)能量優(yōu)化設(shè)計_第2頁](http://file4.renrendoc.com/view10/M02/08/38/wKhkGWV6uESAOJXOAALtpmOJZqE5152.jpg)
![無線傳感器網(wǎng)絡(luò)能量優(yōu)化設(shè)計_第3頁](http://file4.renrendoc.com/view10/M02/08/38/wKhkGWV6uESAOJXOAALtpmOJZqE5153.jpg)
![無線傳感器網(wǎng)絡(luò)能量優(yōu)化設(shè)計_第4頁](http://file4.renrendoc.com/view10/M02/08/38/wKhkGWV6uESAOJXOAALtpmOJZqE5154.jpg)
![無線傳感器網(wǎng)絡(luò)能量優(yōu)化設(shè)計_第5頁](http://file4.renrendoc.com/view10/M02/08/38/wKhkGWV6uESAOJXOAALtpmOJZqE5155.jpg)
版權(quán)說明:本文檔由用戶提供并上傳,收益歸屬內(nèi)容提供方,若內(nèi)容存在侵權(quán),請進行舉報或認領(lǐng)
文檔簡介
無線傳感器網(wǎng)絡(luò)能量優(yōu)化設(shè)計
1案例4:德國兩,4.3.4與4.5inraftingraftingraftingraftingraftingraftingdrinci生物,ro無線通信的sensor網(wǎng)絡(luò)有更多的應(yīng)用,即無線通信的流暢行動應(yīng)用,這也是一個適用的結(jié)果,即家庭成員的安裝、環(huán)境管理、安全和互聯(lián)網(wǎng)生活運營商。Sensorsarecapableofmonitoringawidevarietyofambientconditionssuchastemperature,pressure,andmotion.Becausesensorsarepoweredbybatteries,energy-efficientofsensorsisamainconcernandamoschallengingtaskforthedesignofwirelesssensornetworks.Inamulti-hopadhocsensornetwork,eachnodeplaysthedualroleofdataoriginatoranddatarouter.Afewnodes’malfunctioningcancauseseriousproblemsthatrequirereroutingofpacketsandreorganizationofthenetwork.Hence,powerconservationandmanagementhaveadditionaimportance.Recently,manyprotocolsandalgorithmsaboutenergy-efficiencyhavebeenproposed.AsreportedinRef.,thecluster-basedhierarchicalmodelisbetterthantheone-hopormulti-hopmodel.ArecentprotocolthaoptimizestheenergyefficiencyinsensornetworksisLowEnergyAdaptiveClusteringHierarchy(LEACH)LEACHisthearchitecturethatinafixedarea,theuniformlydistributedsensornodesareformingadaptiveclustersandrotatingclusterheadpositionsrandomlytoevenlydistributetheenergyloadamongthesensorsinthenetwork.Duetothelimitedenergyandotherresources,thenodeswillrepresentafeaturethatmaximizestheirownbenefits,whichmakethemnotpositivelyfollowthecommonassumptions.Thisfeatureissimilartotheauctiontheoryofageneralizedsecondbestsealedbidaction.Moreover,inadversaryenvironment,theremayexismaliciousnodesthatnotonlymayrejecttoreporttheirtrueenergybutalsomaydisturborevendestroythenetwork.Wecallthecharacteroftheformerself-interestorselfishness,andthelatermalice.Theselfishcharactercommonlyexistsinthecivilsensornetworks,whilethemalicemainlyexistsinmilitarynetworks.Inthispaper,weonlyconsidertheself-interestcharacterofsensornodes.Duetotheself-interestcharacter,thenodesmaynotreportheirenergytruthfullyandforwardtherelaydataactively,thatwillmakethenetwork’stopologychangefrequentlyThebehaviorofselfishnodescanbemodeledbygametheoryandtheselfishnodescanbecalledselfishagents.Toachievedesiredproperties,mostpapersassumethatnodescooperatewitheachotherbyfollowingthewell-definedprotocols,regardlessoftheselfishcharacterofnodes.InspiredbythegametheoryandmechanismdesigntheoryinRef.,westudytheselfishlyconstructednetworksbymodelingenergyreportasamechanismdesign,andbasedonthetrulyreportedenergy,formtheclusters.Inthisnon-cooperativegame,wedevelopsuchamechanismthatalignsthegoalsofselfishindividualsensorswiththeglobalgoalsoftheentirenetwork.Insuchanapproach,sensorswithinthenetworkareassumedtoberationalandnodesmakinglocaldecisionsincreasetheirownutility.Themechanismensurestheglobalgoalandmaximumnetworklifetimewhentheselfishsensorstruthfullyreporttheirenergy.2“非-cooperation”laheningOneofthemostcriticalissuesindesigningsensornetworkalgorithmsistominimizetheenergyconsumptionwhilemeetingcertainperformancerequirementssuchasdelayandthroughput,etc.Manyresearchershavefocusedonissueslikeenergyawarerouting,energysavingthroughactivationofalimitedsubsetofnodes,andproposedprotocolsandalgorithmsincludingenergyefficiency.Clusteringinwirelesssensornetworkisahottopic.Acluster-basedroutingprotocolgroupssensornodesinordertoefficientlyrelaythesenseddatatothesink.Eachgroupofsensorshasaclusterheadthatisaspecifiednodebeinglessenergy-constrained.Clusterheadsaggregatethereceiveddataandsendthemtothesink.Clusterformingisamethodthatminimizesenergyconsumptionandcommunicationlatency.ThreemostwellknownhierarchicaroutingprotocolsareLEACH,TEENandChain-based3levelPEGASIS.However,mostproposedapproacheshavetoomanyassumptionsonsensornodes.Forexample,nodesmusthavethesameinitialenergylevel,nodesarestatic,ornodesshouldhavemuchinformationaboutothernodes.Theseassumptionsarenopracticalinreality.OtherproblemssuchasinLEACHtheclusterheadiselectedbasedonaround-robinstrategyThisstrategywillchangethetopologyofclustersfrequentlybecausetheselectedclusterheadmayhaslessenergyEverytime,theclusterheadchangingproducesalargeoverheadsinceallthenodesinthisclusterhavetobenotified.Besides,mostoftheproposedclusteringprotocolsdonotconsidertheselfishnessofthenodes.Forapracticasensornetworksthatneedutmostcooperation,especiallythosethatarecontrolledremotely,theselfishnodeswilreluctanttotelltheirprivateinformation,suchastheirownenergy.Selfishnessinwirelessnetworksisstudiedonlyrecently.Mostapproachesfallintotwocategories:rewardingthecooperativenodesorpunishingnon-cooperativenodes.Bothcategoriesfocusondataforwardingstrategiesbetweennon-cooperationnodes.Inthenextsectionweextendtheideatotheclusterformation.Ourgoalistodesignanadaptive,energy-efficient,hierarchicalclusterformationalgorithmthatmaximizesthelifetimeofthesensornetworksbyselectingthemostpowerfulclusterheads.Theselfishnessofthesensornodesismodeledbygametheory,morespecifically,themechanismdesignismodeledbydesigningagamesuchthatselfishbehaviorofthenodesinducesapredictablestrategyprofile,andtheoutputfunctionforthispredictedstrategycorrespondstotheoutcome,calledsocialchoiceoptimum.Inotherwords,thegameshouldbedesignedinsuchawaythatchoosingthepredefinedstrategythatresultsinthesociachoiceoptimumisadominantstrategyforeachnode.Heredominantmeansthatnonodehasanincentivetounilaterallydeviatefromthestrategy.Ifallnodesselectadominantstrategyfromthestrategyprofile,thenthecombinationofeachnode’sdominantstrategyiscalleddominantstrategyequilibrium.Ourgoalofmechanismdesignistodefinerulessuchthatthesocialchoiceoptimumisdominant-strategyequilibrium.Therestofthepaperisorganizedasfollows.Section3introducesthebasicmechanismdesigntheory.InSection4,weproposetheclusteringalgorithmwithoutconsideringtheselfishnessofnodes,andanalyzethecompactofselfishnesstoclusteringperformance.Thenwegivetheclustermechanismdesignstrategythatcanbeappliedtoourclusteringalgorithm.InSection5,wepresentsimulationresultsaboutouralgorithmwithandwithoutheselfishnodes.Theresultsshowabetterclusteringperformancecanbeachievedwithourmechanismdesignstrategyforselfishnetwork.InSection6,wegiveconclusions.3n-t回歸系數(shù)Inthissectionweintroducesomestandardnotionsformechanismdesign.Wealsodiscussthedominanstrategyimplementationinquasi-linearenvironmentdescribedinRef..Assumetherearennodes,eachnodeihasitsprivateinformationti∈Ti(termeditstypeorenergy)thatmapstothemechanism’soutputspecificationo∈O,hereOisthesetofallowedoutputs.Eachnodeihasapreferencereavaluedfunctionvi(ti,o),calleditsvaluation.Definition1.AmechanismM=(O,P)iscomposedoftwoelements:Anoutputfunctiono(),andann-tupleofpaymentsp1,p2,…,pn.Specifically:1.ThemechanismdefinesafamilyofstrategiesSiforeachnodei.Nodecanchoosesi∈Sitoperformtheoutputfunctiono(s1,s2,…,sn).Themechanismdefinesapaymentpi=pi(s1,s2,…,sn)toeachnode;2.Whenthemechanismtransfersthepaymentpitonodeifortheoutputo,thenode’sutilitywillbeui=vi(ti,o)+pi.Thisutility*iswhatthenodeaimstooptimize;3.Wesayamechanismisanimplementationwithdominantstrategies(orinshortjustanimplementation)ifforeachnodeiandti,thereexistsastrategysi∈Si,calleddominant,suchthatforallpossiblestrategiesoftheothernodess-i,simaximizesnodei’sutility.i.e.,foreveryis′∈Si,ifwedefineo=o(si,s-i)**,o′=o(is′,s-i),pi=pi(si,s-i),ip′=pi(is′,s-i),thenvi(ti,o)+pi≥vi(ti,o′)+ip′.Thenwesayforeachtupleofdominantstrategiess=(s1,s2,…,sn),theoutputfunctiono(s)satisfiestheoutputspecification.Thesimplesttypeofmechanismsisthatthenodes’strategiesaresimplytoreporttheirtypesorenergy.Definition2.Wesaythatamechanismistruthfulif1.Forallnodei,andallti,Si=Ti,i.e.,thenodes’strategiesaretoreporttheirtrueenergy.(Thisiscalledadirectrevelationmechanism);2.Truthtellingisadominantstrategy,i.e.,si=tisatisfiesthedefinitionofadominantstrategyabove.Definition3.Wesaythatamechanismisstronglytruthfuliftruthtellingistheonlydominantstrategy.ThemostimportantimplementationofmechanismdesigniswhatisusuallycalledthegeneralizedVickrey-Clarke-Groves(VCG)mechanism(Vickrey(1961);Clarke(1971);Groves(1973)).TheVCGmechanismappliestothemechanismdesignmaximizationproblemswheretheobjectivefunctiong(o,t)issimplythesumofallnodes’valuations.Thesetofpossibleoutputsisassumedtobefinite.Definition4.AmaximizationmechanismdesignproblemiscalledutilitarianifitsobjectivefunctionsatisfiesDefinition5.Wesaythatadirectrevelationmechanismm=(o(t),p(t))belongstotheVCGfamilyifTheorem(Groves(1973)).AVCGmechanismistruthful.4ransmisonforasWeconsiderafullydynamicnetworkandallcommunicationbetweenclustersisthroughclusterheadssatisfyingthefollowingassumptions:(1)Thesinknodeislocatedinthecenterofthenetwork;(2)Allnodesinthenetworkhavedifferentenergylevelsandhavenolocationinformation;(3)Thenode’stransmissionradiusislineartoitsenergy;(4)Nodescanadjustthepowerlevelfortransmissionandcanvarythetransmissionrange;(5)Linksareasymmetric.I.e.,nodeiwithhigherenergycanreachnodejthatisfallwithini’stransmissionradius,whilenodejmaynotreachnodeibecauseofitslowenergy.WemodelthewirelesssensornetworkconsistingofasetofnodesN=(n1,n2,…,ni,…)thatareuniformlydistributedinasquarearea.Nodesshareacommonwirelesschannelbyusingomni-directionalantennas.Wedividethelarge-scalesensornetworkintoclusteredlayers.Allnodesaregroupedintoclusters.Eachclustervotesaclusterhead.Tosaveenergyanddecreasethedataredundancy,datashouldfirstaggregateincurrentclusterthenbesenttoalower-levelclusterheaduntilitreachesthesinknode.Asdatamovesfromahigher-leveltoalowerone,ittravelsgreaterdistances,thusreducingthetraveltimeandlatency.Afterinitializationofthesensornetwork,ouralgorithmformsclustersandchoosesoneclusterheadforeachclusterthathasthemaximumenergylevel.Inordertodetermineclusterheads,weneedamechanismtoreconfiguretheclusters.WeusetheideasofweightedclusteringapproachdescribedinRef..4.1receificity,清水景,其他相關(guān)文件whereKisaconstant,di,jisthedistancebetweennodesiandj,whichisalsothecommunicationradiusofnodei,andαisthedistance-powergradientvaryingbetweenoneandsixdependingontheenvironmentconditionsofthenetwork.Ourmechanismwillensurethenodetoreportitsmaximumtransmissionpowerwhenitperformstheclusteringalgorithm.Forsimplicity,weconsidertheidealconditioninEq.(1)thatcomesK=1,α=2forthedistance-powergradientofthefreespace.Accordingtothereceiversensitivity,eachnodehasaminimalreceivingpowerthatistheminimalsignalstrengthtoreceivesignals.Forsimplicityofouralgorithm,weassumeallnodeshavethesamereceiversensitivity,thusrecrecjreciPPPminmin,min,==.Ifnodej’sminimalreceivingpowerisrecjPmin,,toassurejreceivingmessagesfromnodei,nodei’stransmissionpowermustbegreaterthanaminimaltransmissionpowertranjiP→min,.ThusFromEqs.(1)and(2),wehaveOncenodejreceivesmessagefromnodei,itcancomputethenodei’sminimaltransmissionpowerbyEq.(3),anditsendsbackamessagetonodeitotelltheminimaltransmissionpoweraswellasitsdefaultpower.Thiscangreatlysavenodei’senergywhenitsendsdatatonodejusingtheminimaltransmissionpower.4.2cluder&非ighbocking/la服er/非igh-非igh-非igh-非好演化/非igh-非好演化非好關(guān)于“cluder-非關(guān)于cluder”/非igh-u.3.3.3.3.3.3.3.3.3.3inchister3.4和laraincisiphincisilit-laraincisiphincisi運行國際,lartrainsiphinsiphinsiinceince.3.3.3.3.3.3.3.3.3.3.3.3.3.3.3.3.3.3.3.3.3.3.3.3.3.3.3.3.3.3.3.3.3.3.3.3.3.3.3.3.3.3.3.3.3.3.3.3.3.3.3.3.3.4.3.4.3.4.5.3.4.5.3.4.5.3.4.5.3.4.5.3.4.5.4.5.4.5.4.5.4.5.4.5.5.4.5.4.5.5.5.4.5.4.5.4.5.4.5.4.5.4.5.4.5.4.5.5.4.5.4.5.4.5.4.5.4.5.4.5.5.4.5.4.5.4.5.4.5.5.4.5.4.5.4.5.4.5.4.5.5.4.5.4.5.4.5.5.4.5.5.5.4.5.5.5.5.4.5.5.5.5.5.5.5.5.5.5.5.5.5.5.5.5.5.5.5.5.5.4.5.5.5.4.5.5.4.5.5.5Ahierarchicalclusteredsensornetworkispartitionedtoanumberofclusters.Nodeiworkingasaclusterheadisdenotedbychi.ThesetofallclusterheadsisdenotedbyCH,CH?N.CurrenthierarchyclusterheadsaredenotedbyasetofCHcur_hier.AlltheclustersofthenetworkaredenotedbyasetofCandcurrenthierarchyclustersaredenotedbyasetofCcur_hier.ThetotalnumberofnodesinCcur_hierisdenoteby|Ccur_hier|.WeuseΓasatemporarysetofstoresforcurrentcluster’smembernodes.Asensorj∈{N-CH}belongstoaclusterciifandonlyifdi,jisminimalamongalltheclusterheadsinCH.Theclusterheadofciischi.Itisclearthat|C|=|CH|.ThememberofclusterciisdenotedbyicM,CHNMiiccC-=∈?U.Nowwedescribeourclusterformationalgorithmindetail.Thealgorithmconsistsoftwostages.Intheinitialstagethesinknodeinitiatestheclusteringprocedure(Fig.1(a)).Hereweassumetherealwaysexistsneighborsofthesinknode.Thisisreasonablesinceweconsiderthenodestobeuniformlydistributed.Theclusterformationstagecanbedividedintotwosimilarsteps.Thefirststep(Lines1~8,Fig.1(b))isthefirsthierarchyclusteringprocess.Thenodethathasthelargestenergywillbeselectedastheclusterheadwithahigherpriority.Howeverthereisalsoanimplicitconditionthatthedistancebetweenthisnodeanditscurrentclusterheadshouldbefartherthanthedistancebetweenthisnodeandtheclusterheadoftheuplevelhierarchy.Whenchiisselectedasaclusterhead,itbroadcastsREQ_ENERGYmessagetoallothernodestoindicateitsdefaultenergyPchidefaultandtransmissionenergyPchitraninthepacketheader.EachneighborjofchireceivingREQ_ENERGYcandetectthereceivingenergyPjrecbythereceivedsignalstrengthindicator(RSSI).AccordingtothetransmissionenergyiPtranandminimalreceivingenergyPminrecofchi,neighbornodejcancomputeitstheminimatransmissionenergyPtranj→chi,minbyEq.(3).NodejthensendsbackREP_ENERGYtochicontainingitsdefaultenergyandminimaltransmissionenergy.WhenchireceivesREP_ENERGYfromallitsneighborsNBRchi,thealgorithmselectsthenodewiththemaximaldefaultenergyasthenexthierarchyclusterhead(Line13,Fig.1(b)).ThenclusterheadchisendsclusteringmessagetoNBRchitonotifytheneighborstojointhecurrentclusterci.Afterclusteringfinishes,thenetworkispartitionedbysomeclustersandseveralhierarchies.Duetothelargerenergyoftheselectedclusterheads,thetopologycankeepstableforalongtime.Andthetransmissionpowerwithinaclustercanbeminimizedbecausetheclustermemberscansenddatatotheirclusterheadsusingtheminimaltransmissionenergy.Sincemostofthepacketsaretransmittedfromclustermemberstoclusterheads,thisgreatlysavesenergy.Thusourclusteringalgorithmisenergy-efficient.Withthenodessendingandreceivingdata,someofthenodesmaybeenergy-depleted.Thenetworkneedsreclustering.Wedesignamonitoringprocesstodealwiththereclusteringprocedure.DifferentfromothertopologycontrolprotocolssuchasLEACH,whichusesaninitialpercentageofeachnodetobeaclusterheadandtheclusteringisexecutedcircularly,ouralgorithmisadaptive.Thereclusteringformationistriggeredwhenneededanditcanoperateinalocalarea.Whenanysensornodedetectsthatitsenergyistoolowtoprovideserviceduringthenetworkoperation,ourreclusteringprocesswillbetriggeredanditoperatesonlyinthecurrentclusterrange.Thisguaranteesthereclusteringprocesstakeslittletimeandrunsefficiently.Weinducethepossiblescenariosthatmaytriggerthenetworkreclusteringasfollows:(i)Ifaclusterheaddetectsitsenergytoolowtosustainthecluster,itwillsenditsneighbornodesamessagetorecluster,anditgivesuptheclusterheadposition.Allthenodesincludingtheclusterheadshouldindividuallyjoinotherexistingclustersorestablishanewcluster;(ii)Iftheclusterheadmovesoutofthecurrentclusterrangebutwithinanotherexistingcluster,thenitmustjointhenewclusterandbeacommonsensornode.Nodeswithincurrentclustermustreconstructanddefineanewcluster;(iii)Ifasensornodemovesoutofthecurrentclusterrangebutwithinanotherclusterrange,transferthesensornodetothelatercluster;(iv)Ifthesensornodemovesoutoftheexistingclusterrangeandisoutofrangeofanyotherexistingcluster,thendefineanewcluster.4.3重新定義squetsPreviousalgorithmisbasedonthenetworkwithhonestnodes.However,foranetworkwithselfishnodestherearisestheproblem:itmaynotbethebestinterestthatnodeipresentsitsemissionsignalstrengthcorrectly.Inreality,forselfishnodes,assertinglargerenergywillresultinahigherpaymentthatthenodereceives.Wediscusstheselfishnessinarealsensornetworkanddesignamechanismthatisfairlyenoughsothattheselfishnodeswilnottrytocheat.Ourgoalistodesignsuchamechanismthatcausesallnodestoacttruthfully,i.e.,torevealtheirtrueprivateinformation.WedesignourmechanismdesignframeworkasFig.2referencedfromRef..Theinputofourmechanismisavectorofstrategiess(t)=(s1,s2,…,sn)thatdependonthetruetypet.Theoutpufunctiono=o(s)correspondstoasocialchoicefunction(SCF),g(o,s).Thepaymentpicomputedbythemechanismistransferredtonodeithatincentsnodeitoreporther***trueenergy.Inthefollowing,weusetheeconomicmechanismdesigntheorytodesignthemechanismforselfishnetwork(Fig.2).AssumethetotalcostoftopologyformationisW.Thenodesvoluntarilycontributew1,w2,…,wnresourcesthacanbeconsideredastheenergyconsumed,andwiisproportionaltonodei’strueenergyPi.Assumenodesbenefifromthetopologywithfixedprofitsr1,r2,…,rn.Oncethetopologyisformed,nodeicangainvi=ri-winetprofitorpreferencevalue.Thusthenecessaryandsufficientconditionfortopologyformationis∑∈>Niiv0.Thatistosay,whethernodeicooperatesornot,herobjectiveistomaximizetheutility.Toensurethenodescooperate,wehavetomaximizetheirutility.Wedenotenodei’sreportedpreferencevaluebyv?i.Sincenodeimaycheat,v?imaynotequaltovi.AccordingtotheVCGmechanism,thetopologyisestablishedwhenthesumofallnodes’preferencevaluesisgreaterthanthesumofalltheircontributions.HenceOurmechanismmustbenefitforthosewhocooperatewithothers.Weassociatethisbenefitwithtransferpaymenttiforeachnode.tiisdeterminedbythefollowingequationwherehi()isanarbitraryfunctionofv?-iandisindependentofv?i.SubstitutingEq.(5)andEq.(6)inEq.(4)withEq.(5),wehavethepayofffunctionTheselfishnodeexpectstogetthetransferpaymentwhatevershecooperateornot.FromVCGmechanism,cooperationforanodeisadominantequilibriumstrategy.i.e.,eachnodewillincentivelytellhertrueenergy.Wecanformulateourresultsasfollows:Lemma1.Ifnodeiwantstojoinacluster,shemusttellhertrueenergyPi.Lemma2.Ifnodeihopesthetopologynottobeformed,shealsomusttellhertrueenergyPi.Weomittheproofoftheselemmasduetothelimitationofspaceofpages.Fromthelemmasweseethattruthtellingisadominantstrategy.Thuswehavethefollowingresult:Theorem.OurVCGmechanismistruthful.Tosimplifyourmechanism,wecandefinethearbitraryfunctionhi()asfollowsThenthetransferpaymentis:Thatmeansthemechanismwillpunishthosewhoseobjectivechangesthesocialchoiceobjective.Inotherwords,themechanismwillforcethenodesthatsatisfy(?)(∑∑?0)<Nii≠∈ijjvvtotransferpaymenttooumechanism.Becauseoftheselfishfeature,nonodewouldliketoreceivepunishment.Thenwhattheycandoistocooperatewiththeirneighbors.5通過sixremaining/rohsremaining表示活動—SimulationandEvaluationWesimulateawirelesssensornetworkof1000and2000nodesusingMATLAB.Theheterogeneoussensorsareuniformlydistributedina1000×1000squaremetersareaandthesinknodeislocatedinthecenterofthenetwork.Weassigneachsensornodeadifferentrandomlygeneratedinitialenergyfrom0.3to0.5Joules.Anodeisconsidereddiedifitsenergylevelreaches0.Wealsoassumethatthechanneliscollisionfree.Inordertomeasuretheenergyconsumptionforcollectingsenseddatafromtheclustermembers,weusedthesameenergymodeintroducedinLEACH,usingradioelectronicsenergyEelec=50nJ/bit,radioamplifierenergyεamp=1000pJ/bit/m2and512bit-sizesenseddatapacket.Wesimulatethetotalenergyconsumedforhigh-densitysensornetworkwhenformingthetopology.Figure3showsourresultfor1000-nodeand2000-node.Thesensornodes’radiorangesarerandomlysetfrom150mto300m.Andthemaximumclusterradiusis300m.FromFig.3,itisclearthattheconsumedenergyforclusteringforLEACHincreasesgreatlywhentheclusterradiusincreases.HowevertheenergyconsumedforDEEHincreasesveryslowly.Forhigh-densitynetwork,energyconsumedforDEEHevendoesnotincreasewithclusterradiusincreasing.SoDEEHismoresuitableforlarge-scalenetwork.Whenselfishnodesexistinthenetwork,itisveryimportanttoassuretheselfishnodestocooperateandteltheirtrueenergy.Wesimulatetheselfishnodesasrandomlyreportingtheirlocalenergyfrom0to0.8Joules.Andweanalyzetheclusterheads’remainingenergydistributionaftertheclusteringprocedureends.Figure4showsthesimulationresultswithdifferentselfishnodesinthenetwork.Becauseoftheselfishnodesinthenetwork,theclusterheadsremainenergyoscillationsgreatly.Aseachnode’sinitialenergyisfrom0.3to0.5Joules,theremainingenergythatislowerthan0.3orgreaterthan0.5canbeconsideredasthedeclaredenergybyselfishnodes.Theselfishnodemayunderdeclareitsenergytosaveenergyoroverdeclaretobeaclusterheadtoacquiremorebenefitfromthemechanism.Bothofthetwodeclarationscancausethetopologyunstable.Ifanodeoverdeclaresitsenergyanditiselectedasclusterhead,sinceitsrealenergyislowitdepletesitsenergyquickly,andthecurrentclustermustreselectaclusterhead.Thismakesthetopologyalterfrequently.Ifanodeunderdeclaresitsenergy,ithardlybecomesaclusterheadalthoughithashighenergy.Thiswillconsumetheclusteringproceduremoreenergytoselecttheclusterhead.FromFig.4,wecanseeth
溫馨提示
- 1. 本站所有資源如無特殊說明,都需要本地電腦安裝OFFICE2007和PDF閱讀器。圖紙軟件為CAD,CAXA,PROE,UG,SolidWorks等.壓縮文件請下載最新的WinRAR軟件解壓。
- 2. 本站的文檔不包含任何第三方提供的附件圖紙等,如果需要附件,請聯(lián)系上傳者。文件的所有權(quán)益歸上傳用戶所有。
- 3. 本站RAR壓縮包中若帶圖紙,網(wǎng)頁內(nèi)容里面會有圖紙預(yù)覽,若沒有圖紙預(yù)覽就沒有圖紙。
- 4. 未經(jīng)權(quán)益所有人同意不得將文件中的內(nèi)容挪作商業(yè)或盈利用途。
- 5. 人人文庫網(wǎng)僅提供信息存儲空間,僅對用戶上傳內(nèi)容的表現(xiàn)方式做保護處理,對用戶上傳分享的文檔內(nèi)容本身不做任何修改或編輯,并不能對任何下載內(nèi)容負責(zé)。
- 6. 下載文件中如有侵權(quán)或不適當內(nèi)容,請與我們聯(lián)系,我們立即糾正。
- 7. 本站不保證下載資源的準確性、安全性和完整性, 同時也不承擔用戶因使用這些下載資源對自己和他人造成任何形式的傷害或損失。
最新文檔
- 2025-2030全球離網(wǎng)房車行業(yè)調(diào)研及趨勢分析報告
- 2025-2030全球高脈沖能量皮秒激光器行業(yè)調(diào)研及趨勢分析報告
- 月齡嬰兒情緒情感與社會性親子活動設(shè)計創(chuàng)造性撫觸游戲講解
- 2025【合同范本】建筑工程設(shè)計協(xié)議書
- 蔬菜配送合作合同范本
- 分期付款合同模板集錦
- 會簽單合同模板
- 全新對講機服務(wù)合同下載
- 勞務(wù)出資合伙協(xié)議合同
- 個人租車租賃合同范本
- 《建設(shè)工程監(jiān)理》課件
- 2019版新人教版高中英語必修+選擇性必修共7冊詞匯表匯總(帶音標)
- 初中八年級音樂-勞動號子《軍民大生產(chǎn)》
- 中層領(lǐng)導(dǎo)的高績效管理
- 小小銀行家-兒童銀行知識、理財知識培訓(xùn)
- 機械基礎(chǔ)知識競賽題庫附答案(100題)
- 閱讀理解特訓(xùn)卷-英語四年級上冊譯林版三起含答案
- 國庫集中支付培訓(xùn)班資料-國庫集中支付制度及業(yè)務(wù)操作教學(xué)課件
- 屋面及防水工程施工(第二版)PPT完整全套教學(xué)課件
- 2023年上海青浦區(qū)區(qū)管企業(yè)統(tǒng)一招考聘用筆試題庫含答案解析
- 2023年高一物理期末考試卷(人教版)
評論
0/150
提交評論