異構(gòu)融合網(wǎng)絡中端到端服務質(zhì)量控制與管理的研究的綜述報告Abstract:Heterogeneousfusionnetwork(HFN)hasrecentlyemergedasapromisingsolutionforintegratingmultipletypesofnetworkstoprovideend-to-endconnectivity.Toensureasatisfactoryqualityofservice(QoS)fornetwork-basedservicesinHFN,effectiveQoScontrolandmanagementmechanismsmustbeimplemented.ThispaperpresentsacomprehensivereviewofrecentresearchthatfocusesonQoScontrolandmanagementinHFN,includingQoSmodels,resourceallocationmethods,andtrafficengineeringtechniques.Wealsodiscusssomeoftheopenissuesandchallengesinthisarea.Introduction:TheHeterogeneousFusionNetwork(HFN)isanovelnetworkarchitecturethatintegratesdifferenttypesofnetworks(e.g.,wired,wireless,cellular,satellite)toprovideaseamlessend-to-endconnectivityforvariousservices.HFNhasgreatpotentialtoimprovenetworkperformanceandprovideubiquitousservicecoverage.However,theintegrationofheterogeneousnetworksposessignificantchallenges,particularlywithrespecttoqualityofservice(QoS)controlandmanagement.IdealHFNsshouldhaveaunifiedQoSframeworktohandletherequirementsofdifferenttypesofnetworksandtoguaranteethecontinuityofservicestomeetcustomerneeds.ThispaperpresentsasurveyofrecentresearchonQoScontrolandmanagementinHFNs,withafocusonQoSmodels,resourceallocationmethods,andtrafficengineeringtechniques.QoSModels:QoSmodelsdefineasetofmetricsforevaluatingtheperformanceofnetworkservices,suchasbandwidth,delay,jitter,andpacketloss.ExistingQoSmodelscanberoughlydividedintothreecategories:(1)deterministicQoSmodels,(2)statisticalQoSmodels,and(3)hybridQoSmodels.DeterministicQoSmodelsarebasedonmathematicalmodelsthatpredictthenetworkbehavior.Thesemodelscanaccuratelypredictnetworkperformanceunderidealconditions,butarelessaccurateinreal-worldscenariosduetouncertaintiesandchangesinnetworkbehavior.StatisticalQoSmodelsarebasedonstatisticalanalysisofnetworktraffic.Theyuseprobabilisticmethodstopredictnetworkbehaviorandusuallyofferhigheraccuracythandeterministicmodelsinreal-worldscenarios.HybridQoSmodelscombinebothdeterministicandstatisticalapproaches.Thesemodelsaremorecomplexthantheothertwotypes,butofferbetteraccuracyandflexibility.ResourceAllocationMethods:ResourceallocationmethodsaimtodistributenetworkresourcesefficientlyaccordingtoQoSrequirements.Differentresourceallocationmethodscanoptimizedifferentmetrics,suchasthroughput,energyconsumption,andfairness.Onecommonmethodiscalledtheproportionalfairscheduler(PFS).PFSallocatesresourcesbasedontheratioofserviceratetoaveragequeuelength.Thismethodcanachievehighthroughputwhilemaintainingfairnessamongusers.Anothermethodcalledthemax-minfairscheduler(MFS)allocatesresourcestomaximizetheminimumrateofallusers.Thisapproachensuresthatlow-priorityusersarenotignoredandoptimizesthefairnessofthesystem.TrafficEngineeringTechniques:Trafficengineering(TE)techniquesareusedtooptimizenetworktrafficandtominimizecongestionanddelay.InHFNs,TEtechniquescanbeappliedtomakeoptimalroutingdecisionsbasedonQoSrequirements.ExamplesofTEtechniquesincludetrafficgrooming,loadbalancing,andtrafficshaping.Trafficgroomingaimstoreducenetworkcongestionbyaggregatinglow-bandwidthtrafficintohigh-bandwidthstreams.Thistechniquecansignificantlyimprovenetworkefficiencyandreducedelay.Loadbalancingdistributestrafficevenlyacrossnetworkresourcestopreventcongestion.Thismethodcanimprovenetworkthroughputandreducedelay.TrafficshapingcontrolstheflowoftrafficintothenetworkbydelayingorqueuingpacketsbasedonQoSrequirements.Thistechniquecanimprovenetworkutilizationandreducedelay.OpenIssuesandChallenges:DespitetheprogressthathasbeenmadeinQoScontrolandmanagementinHFNs,severalchallengesandopenissuesremain.OnechallengeisthelackofunifiedQoSmodelsandmetricsthatcanbeusedacrossalltypesofnetworks.ThediversityofnetworksandQoSrequirementsmakesitdifficulttodevelopaunifiedQoSframework.AnotherchallengeisthecomplexityandscalabilityofQoScontrolandmanagementmechanisms.HFNsaretypicallylargeandcomplex,whichcanmakeitdifficulttodesignefficientQoScontrolandmanagementmechanismsthatcanhandlethedemandsofdiverseservices.Conclusion:ThispaperpresentedacomprehensivereviewofrecentresearchonQoScontrolandmanagementinHFNs.QoSmodelsplayanessentialroleinensuringsatisfactorynetworkperformance,whileresourceallocationmethodsandtrafficengineeringtechniquescanoptimizenetworkresourcesandreducecongestionanddelay.However,challengesand