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车联网中基于停车协同的边缘计算卸载方法.docx

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车联网中基于停车协同的边缘计算卸载方法 Title:EdgeComputingOffloadingMethodsbasedonParkingCoordinationinVehicularNetworks Abstract: Vehicle-to-vehicle(V2V)communicationandtheInternetofVehicles(IoV)havegainedsignificantattentionduetotheirpotentialtoimproveroadsafetyandtrafficefficiency.Theintegrationofedgecomputinginvehicularnetworksenablestheprocessingandanalysisofdataatthenetworkedge,reducinglatencyandimprovingsystemperformance.ThispaperproposesanoveledgecomputingoffloadingmethodbasedonparkingcoordinationinV2Vnetworks,aimingtooptimizetheallocationofcomputingresourcesandalleviatenetworkcongestion. 1.Introduction Theincreasingnumberofvehiclesontheroadhasledtoincreasedtrafficcongestionandtheneedforefficientroadmanagementsystems.Vehicularnetworksandedgecomputingtechnologieshaveemergedaspotentialsolutionstoaddressthesechallenges.Thispaperexplorestheintegrationofparkingcoordinationandedgecomputingtoenableefficientoffloadingofcomputationaltasksinvehicularnetworks. 2.RelatedWork Previousresearchhasfocusedonvariousaspectsofvehicularnetworksandedgecomputing.Somestudiesinvestigateoffloadingtechniquesbasedontheavailabilityandproximityofnearbyvehiclesorroad-sideunits(RSUs).Othersexploretheuseofcloudcomputingforresourceallocation.However,limitedresearchhasaddressedthecoordinationofparkingspacesandedgecomputingoffloadinginvehicularnetworks. 3.EdgeComputingOffloadingMethodbasedonParkingCoordination 3.1.SystemArchitecture Weproposeanovelsystemarchitecturethatintegratesparkingcoordinationandedgecomputinginvehicularnetworks.Thearchitectureconsistsofthreemaincomponents:vehicles,RSUs,andcloudservers.VehiclesactasdatasourcesandoffloadcomputationaltaskstonearbyRSUsorcloudserversbasedontheirlocationandavailablecomputingresources. 3.2.ParkingSpaceAllocation Tooptimizetheoffloadingprocess,aparkingcoordinationalgorithmisdevelopedtoallocateparkingspacesforvehiclesbasedontheiroffloadingrequirementsandtheavailabilityofnearbyRSUs.ThealgorithmaimstominimizethedistancebetweenvehiclesandRSUswhileensuringfairallocation