端到端网络流量的混合估计方法-论文.pdf

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1、第43卷第7期光子学报Vo1．43No．72014年7月ACTAPHOToNICASINICAJuly2014doi：10．3788／gzxb20144307．0706023端到端网络流量的混合估计方法蒋定德，赵祖耀，许宏伟，王兴伟(东北大学信息科学与工程学院，沈阳110819)摘要：利用主成分分析法获取端到端网络流量的主要特征分量并获得其初始估计结果．为克服其初值敏感性将估计结果作为遗传算法的初始值、链路流量估计偏差作为遗传算法的适应度函数，通过构建合适的交叉和变异概率函数来控制遗传算法的交叉

2、和变异过程．采用合适的约束迭代函数，利用遗传算法通过迭代寻优获得端到端流量的估计结果，仿真结果表明所提出的方法是可行的．关键词：端到端流量；流量估计；主成分分析；迭代过程；流量建模中图分类号：TP393文献标识码：A文章编号：1004—4213(2014)07—0706023—6MixedEstimationApproachtoEnd-to—EndNetworkTrafficJIANGDing—de，ZHAOZu—yao，XUHong—wei，WANGXing—wei(College0，form

3、ationScienceandEngineering，NortheasternUniversity，Shenyang110819，China)Abstract：Principalcomponentanalysiswasexploitedtoextracttheprincipalfeaturesofend-to-endnetworktrafficandtoattaintheinitialestiamtionresults．Thisresultsaretakenasthepriorvalueofge

4、neticalgorithmtoovercomeitssensitivenesstothepriorvalue．Theestiamtionbiasesoflinktrafficisregardedasthefitnessfunctionofgeneticalgorithm．Thecrossoverandmutationprobabilityfunctionsarebuilttocontro1itscorossoverandmutationprocesses．Theappropriateitera

5、tivefuntionwithcontraintsisbuilt．Thegeneticalgorithmisusedtoattaintheend-to—endtrafficestimationresultsintheiterativeway．Simulationresultsshowthattheproposedmethodisfeasible．Keywords：End—to—endtraffic；Trafficestimation；Principalcomponentanalysis；Iter

6、ativeprocess；TrafficmodelingoCISCodes：060．4256；060．4251；060．4258；060．1155networkmanagementandtrafficengineering．Dueto0Introductionthedifficultyindirectlyattainingthem，end-to-endwiththerapiddevelopmentofinformationtrafficestimationhasreceivedmoreatten

7、tionfromtechnologies，communicationnetworksarebecomingresearchersandoperatorsaroundtheworldE．moreandmorecomplexandtheirscalesareTheestimationmethodsinRefs．F7—9]isbasedonincreasingl_l_2]．Thenetworktrafficpresentsallkindsofstatistica1theoriestobeputforw

8、ard．Theyusedthenewfeatures。suchasspatio—temporalcorrelationstatisticalmodelstosetupnetworks"source-destinationfeatures，self-similaritynature，heavy-tailednodeflowmodelandexploitedthestatisticaltheorytodistributionandsoon[]．End_to—endtrafficshowstheest