简介：Acompressionalgorithmisproposedinthispaperforreducingthesizeofsensordata.Byusingadictionary-basedlosslesscompressionalgorithm,sensordatacanbecompressedefficientlyandinterpretedwithoutdecompressing.Thecorrelationbetweenredundancyofsensordataandcompressionratioisexplored.Further,aparallelcompressionalgorithmbasedonMapReduce[1]isproposed.Meanwhile,datapartitionerwhichplaysanimportantroleinperformanceofMapReduceapplicationisdiscussedalongwithperformanceevaluationcriteriaproposedinthispaper.Experimentsdemonstratethatrandomsamplerissuitableforhighlyredundantsensordataandtheproposedcompressionalgorithmscancompressthosehighlyredundantsensordataefficiently.

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简介：由于连接增加，小世界现象在基于树的无线传感器网络存在。基于树的网络的小世界上的流行病被学习，并且流行病的爆发在发生的流行阀值是计算的。当感染概率比过滤阀值大时，流行病学的过程被分析。尽管不同流行病学的过程发生在内在的树拓扑学上，当感染传播，感染的节点的数字指数地增加。一致免疫过程在同类的小世界的网络被进行。尽管免疫有效地减少流行速度，感染仍然指数地延长。

简介：我们由分析推理和随机的模拟在一个单个阀值的传感器系统在随机的回声上调查alpha马厩噪音的效果。随机的回声在alpha马厩噪音环境发生在阀值系统，这被显示出，但是反响的效果变得作为alpha马厩索引减少或alpha马厩分发增加的偏斜度参数变弱。特别地，为Cauchy噪音，在最佳的噪音偏差参数，信号振幅和阀值之中的一种非线性的关系是为输出signal-to-noise比率使用极端值条件获得并且说明的经分解。在这通讯介绍的结果应该在non-Gaussian在信号察觉和图象恢复有申请吵闹的环境。

简介：Amethodofdetectingdry,icyandwetroadsurfaceconditionsbasedonscanningdetectionofsinglewavelengthbackwardpowerisproposedinthisletter.Thedetectorisusedtoreceivethebackwardscatteredpowerwhichchangeswiththeincidenceangle.Therelationshipbetweenbackwardpowerandincidenceangleisusedtofindouttheeffectiveanglerangeanddistinguishmethod.Experimentandsimulationshowthatitisfeasibletoclassifythesethreeconditionswithinincidenceangleof5.3degree.

简介：Wirelesssensornetworks(WSNs)arebasedonmonitoringormanagingthesensingareabyusingthelocationinformationwithsensornodes.Mostsensornodesrequirehardwaresupportorreceivepacketswithlocationinformationtoestimatetheirlocations,whichneedslotsoftimeorcosts.Inthispaperweproposedalocalizationmechanismusingamobilereferencenode(MRN)andtrilaterationinWSNstoreducetheenergyconsumptionandlocationerror.Thesimulationresultsdemonstratethattheproposedmechanismcanobtainmoreunknownnodeslocationsbythemobilereferencenodemovingschemeandwilldecreasestheenergyconsumptionandaveragelocationerror.

简介：Anopticalfibersensorforultrathinlayersensingbasedonshort-rangesurfaceplasmonpolariton(SRSPP)isproposed,andthesensingcharacteristicsaretheoreticallyanalyzed.Simulationresultsindicatethatevenforadetectinglayermuchthinnerthanthevacuumwavelength,aresolutionashighas3.7×10-6RIUcanbeobtained.Moreover,anaveragethickness-detectionsensitivityof6.2dB/nmisobtained,whichenablesthesensortodetectthethicknessvariationoftheultrathinlayeruptotensofnanometers.Thesensitiveregionofthicknesscouldbeadjustedbytuningthestructureparameters.

简介：basedonoptimaldesignonthecoreelementofthesensor,awirelessandpassivesurfaceacousticwave(SAW)temperaturesensorintegratedwithIDTagwaspresented.Areflectivedelayline,whichconsistsofatransducerandeightreflectorsonYZLiNbO3substrate.Wasfabricatedasthesensorelement,inwhich,threereflectorswereusedfortemperaturesensing,andtheotherfivewerefortheIDTagusingphaseencoding.Singlephaseunidirectionaltransducers(SPUDTs)andshortedgratingwereusedtostructurethesAWdevice,leadingtoexcellentsignaltonoiseratio(SNR).TheperformanceoftheSAWdevicewassimulatedbythecouplingofmodes(COM)priortofabrication.Usingthenetworkanalyzer,theresponseintimedomainofthefabricated434MHzSAWsensorwascharacterized,themeasuredS11agreeswellwiththesimulatedone,sharpreflectionpeaks,highsignal/noise,andlowspuriousnoisebetweenthereflectionpeakswereobserved.UsingtheradarsystembasedonFSCWasthereaderunit.thedevelopedSAWtemperaturesensorswereevaluatedwirelessly.Excellent1inearityandgoodresolutionof士1℃wereobserved.

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简介：Underwatersensornetwork(UWSN)adoptsacousticcommunicationwithmoreenergy-consumptionandlongerpropagation-delay,whichbringgreatchallengestoprotocoldesign.Inthispaper,weproposedlevel-basedadaptivegeo-routing(LB-AGR)protocol.LB-AGRdividestrafficsintofourcategories,androutesdifferenttypesoftrafficinaccordancewithdifferentdecisions.Packetsupstreamtothesinkareforwardedunicasttothebestnext-hopinsteadofbroadcastingtoallneighbornodesasinpresentUWSNroutingprotocols.LB-AGRdefinesanintegratedforwardingfactorforeachcandidatenodebasedonavailableenergy,density,location,andlevel-differencebetweenneighbornodes,whichisusedtodeterminethebestnext-hopamongmultiplequalifiedcandidates.Throughsimulationexperiments,weshowthepromisingperformanceofLB-AGR.

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