基于概率传输无线传感网数据汇聚方案

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1、基于概率传输无线传感网数据汇聚方案　　摘要：针对传统无线传感网数据汇聚中通信开销较大的问题，提出了基于概率传输的无线传感网数据汇聚方案。由于簇内节点有限，汇聚误差难以避免，在可容忍汇聚误差下，簇内节点按概率进行数据发送，可有效减少簇内消息传输量，降低通信开销。同时，采取狄克逊准则对小样本中的粗大误差进行剔除提供高的簇内汇聚可靠性。实验结果表明，在可容忍误差下进行概率发送可有效降低簇内消息传输量，所提方案的簇内数据汇聚通信开销约为传统方案的27.5%；概率发送的汇聚误差与所有节点进行数据发送的汇聚误差基本在同一水平，都是传感器网络可接受的。关键词：传感

2、器网络；数据汇聚；小样本；可容忍误差；粗差检测中图分类号：TP301文献标志码:A英文标题Probabilistictransmittingbaseddataaggregationschemeforwirelesssensornetworks英文作者名GUOJianghong1*,LUOYudong1,LIU5Zhihong2英文地址(1.SchoolofComputerScience,JiayingUniversity,MeizhouGuangdong514015,China;2.SchoolofComputerScienc

3、eandTechnology,XidianUniversity,XianShaanxi710071,China英文摘要)Abstract：Forreducingthecommunicationoverheadoftraditionaldataaggregationmethodinwirelesssensornetworks,theauthorsproposedaprobabilistictransmissionbaseddataaggregationschemeforWirelessSensorNetwork(WSN).Duetolimitednu

4、mberofnodesintheclusterandthefactthataggregationerrorisunavoidable,probabilistictransmissionwasadoptedtoreducethenumberofinnerclustertransmissionsandlowerthecommunicationoverheadwithtolerableerror.Besides,Dixoncriterionwasadoptedtoeliminatethegrosserrorinthesmallsampletoprovideh

5、ighreliabilityofinnerclusteraggregation.Theexperimentalresultsshowthatthe5probabilistictransmissioncanlowertheinnerclustertransmissionseffectivelywithtolerableerror,thecommunicationoverheadofproposedschemeisabout27.5%thatoftraditionaldataaggregationschemes.Theaggregationerrorof

6、probabilistictransmissionandallnodestransmissionareatthesamelevelandbothareacceptableforwirelesssensornetworks.Forreducingthecommunicationoverheadoftraditionaldataaggregationmethodinwirelesssensornetworks,theauthorsproposedaprobabilistictransmittingbaseddataaggregationschemeforW

7、irelessSensorNetwork(WSN).Duetolimitednumberofnodesintheclusterandaggregationerrorisunavoidable,probabilistictransmittingcanbeadoptedtoreducethenumberofinnerclustertransmissionsandlowerthecommunicationoverheadwithtolerableerror.Also,Dixoncriterionwasadoptedtoeliminatethegrosserr

8、orinthesmallsampletoprovidehighreliabili