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UDN中MEC的资源分配和任务卸载联合优化.docx

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UDN中MEC的资源分配和任务卸载联合优化 Title:JointOptimizationofResourceAllocationandTaskOffloadinginUDN-basedMEC Abstract: ThedeploymentofMobileEdgeComputing(MEC)hasrevolutionizedthewaycomputation-intensivetasksarehandledinmobilenetworks.ThispaperaddressestheproblemofjointlyoptimizingresourceallocationandtaskoffloadinginUltra-DenseNetworks(UDN)utilizingMEC.Thegoalistomaximizetheoverallnetworkperformancewhileminimizinglatencyandenergyconsumption.WeproposeajointoptimizationframeworkthatconsidersboththeallocationofcomputingresourcesandtheoffloadingdecisionoftasksfrommobiledevicestonearbyMECservers.Theproposedframeworkleveragesmathematicaloptimizationtechniquestoformulatetheproblemandprovidepracticalsolutions. 1.Introduction MobileEdgeComputing(MEC)hasemergedasapromisingtechnologyformeetingtheincreasingdemandforlowlatencyandhigh-throughputapplicationsinultra-densenetworks.Bymovingcomputationandstorageresourcesclosertousers,MECenablesreal-timedataprocessing,improvesuserexperience,andreducesnetworkcongestion.However,challengesarisewhenitcomestoefficientlymanagingcomputingresourcesandtaskoffloadinginUDN-basedMECsystems. 2.RelatedWork Thissectionprovidesanoverviewoftheexistingliteratureonresourceallocationandtaskoffloadinginmobilenetworks.Variousapproaches,includingcentralizedanddistributedresourceallocationalgorithms,aswellasdifferenttaskoffloadingstrategies,arediscussed. 3.SystemModel Wepresentasystemmodelthatconsidersanultra-densenetworkwithmultiplemobiledevicesandMECservers.Themodeltakesintoaccountthecharacteristicsofdifferenttypesoftasks,includingcomputationalrequirementsandlatencyconstraints. 4.ProblemFormulation Basedonthesystemmodel,weformulatethejointoptimizationproblemasamixed-integernonlinearprogrammingproblem.Theobjectiveistomaximizeoverallnetworkperformancewhilesatisfyingtaskrequirementsandresourceconstraints. 5.ResourceAllocationandTaskOffloadingAlgorithm WeproposeanefficientalgorithmthateffectivelyallocatescomputingresourcesanddecideswhichtasksshouldbeoffloadedtonearbyMECser