泊松分布下无线传感器网络多目标覆盖控制

1、泊松分布下无线传感器网络多目标覆盖控制收稿日期:20130118;修回日期:20130224。基金项目：北京市教育委员会共建项目。徐奕昕（1990-）,女，江西景德镇人，硕士研究生，主要研究方向：无线传感器网络；白焰（1954-）,男，辽宁沈阳人，教授，博士生导师，主要研究方向：智能系统、工业现场总线、无线传感器网络；赵天阳（1989-）,男，河南南阳人，硕士研究生，主要研究方向：电动汽车、电力系统分析；王仁书（1986-）,男，福建福州人，博士研究生，主要研究方向：无线技术在工业控制系统中的应用。针对无线传感器网络中k重覆盖率、能耗、可靠性难以协调的问题，在节点呈泊松分布的假设下，提出了多目

2、标优化的覆盖控制。针对多目标差分进化算法在种群初始化、参数控制和种群维护中的不足，分别设计了种群正交初始化、参数自适应控制和动态种群维护策略，提出了改进的多目标差分进化（IDEM。）算法对模型进行求解。仿真结果表明，该控制策略能够在达到81.2%的3重覆盖率的同时有效降低能耗弁保障可靠性，IDEM0可以支配传统算法76%勺Pareto前沿。该算法同样适用于求解其他多目标问题。英文标题Multiobjectivecover过gecontrolinwirelesssensornetworkbasedonPoissondislnbllLion英文作者名XUYixin1*TBAIYanbZILWTia

3、nyang2,WANGRenshu1英文地址(1.SchoolofControlandComputerEngineering,NorthChinaElectricPowerUniversity,Beijing102206,China:Amultiobjectiveoptimizationcoveragecontrolwasproposedforsolvingtheintractableproblemofkcoveragercito,energyconsumptionandreliabilityinwirelesssensornetworksontheassumptionthatnodesare

4、inPoissondistribution.Inordertoovercometheshortcomingsofpopulationinitialization,parametercontrolandpopulationmaintcnEinccinmultiobjectivedifferentialevolutionalgorithm,theauthordesignedtacticsofswarmorthogonalinitialization,parameterselfadaptivecontrolanddynamicswarmmaintengineestrategyseparaLely;社

5、ndanimprovedmulLiobjectivedifferentialevolutionsalgoriT.hm(1DKMOJwasproposedtosolvethismodel.Theresultsshowthatthecontrolstrategycaneffectivelyachievethethreecoveragerateof81.2%,reducetheenergyconsumptioneffectively,andensurethereliability.Thisalgorithmcandominate76%Paretofrontsofthetraditionalalgor

6、ithmandbeappliedtothesolutionofothermultiobjectiveproblems.Amultiobjectiveoptimizationcoveragecontrolwasproposedforsolvingtheintractableproblemofkcoveragerate,energyconsumptionandreliabilityinwirelesssensornetworksontheassumptionthatnodewaspassiondistribution.Aimingtoovercomeshortcomingsofpopulation

7、initialization,parametercontrolandpopulationmaintcriH.nccinmultiobjectivedifferentialevolutionalgorithm,theauthordesignedtacticsofswarmorthogonalinitialization,parameterselfadaptivecontrolanddynamicswarmmaintenancestrategyseparately,andanimprovedmultiobjectivedifferentialevolutional<dg()rilhm(lDEMO)waspresentedtosolvethismodel.Theresultshowsthatthecontrolstrategycaneffectivelyachievethe3coverager过teof81.2%andreducetheenergyconsumptioneffectivelyensuringreliabilityinthemeantim