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1、The28thInternationalConferenceonDistributedComputingSystemsDataEstimationinSensorNetworksUsingPhysicalandStatisticalMethodologiesYingshuLiChunyuAiWiwekP.DeshmukhYiweiWuDepartmentofComputerScienceGeorgiaStateUniversity,Atlanta,GA30303{yli,chunyuai,wdeshmukh,wy
2、w}@cs.gsu.eduAbstractinthevisibleandNIRrangeinsidegreenhouses.Thelightintensitycanbemeasuredbythesesensors,anddataestima-WirelessSensorNetworks(WSNs)areemployedinmanytiontechniquesemployedinsuchenvironmentswouldhelpapplicationsinordertocollectdata.Onekeychall
3、engeisconserveenergyandprolongnetworklifetime.Commercialtominimizeenergyconsumptiontoprolongnetworklife-lightsensorswhichusephotodiodesthatproduceavoltagetime.Aschemeofmakingsomenodesasleepandesti-proportionaltothelightintensityarenowavailable.Sim-matingtheir
4、valuesaccordingtotheotheractivenodesilarly,lightintensitysensorsarerequiredtomonitormain-readingshasbeenprovedenergy-efficient.Forthepur-tenanceofoptimumlightinginanimalhusbandryrelatedposeofimprovingtheprecisionofestimation,wepro-business[1],andalsoincell-cul
5、tureexperiments[10]underposetwopowerfulestimationmodels,DataEstimationus-artificiallight,wherealsodataestimationtechniqueswouldingPhysicalModel(DEPM)andDataEstimationusinghelpenhancethelongevityofWSNs.StatisticalModel(DESM).DEPMestimatesthevaluesofsleepingnode
6、sbythephysicalcharacteristicsofsensedat-Usually,userscanacceptapproximatedata.Asaresult,tributes,whileDESMestimatesthevaluesthroughthespa-amethodofdataestimationisaperfectoptionforconserv-tialandtemporalcorrelationsofthenodes.Experimentalingenergy.Infact,thek
7、eychallengeishowtoprovideesti-resultsonrealsensornetworksshowthattheproposedtech-mateddatawithhighprecisionwhileconsumingaslittleen-niquesprovideaccurateestimationsandconserveenergyergyaspossible.Toaddressthisproblem,twonoveldataes-efficiently.timationmethodsa
8、reproposedinthispaper.Inourscheme,aminimalnumberofnodesaresettobeactiveandtheothernodesaresettosleep.Allnodesserveasactivework-ingnodesbyturns.Thebasestationestimatesvaluesof1Introduction