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DOI: 10.4018/JOEUC.2019070103
Journal of Organizational and End User ComputingVolume 31 • Issue 3 • July-September 2019
Copyright©2019,IGIGlobal.CopyingordistributinginprintorelectronicformswithoutwrittenpermissionofIGIGlobalisprohibited.
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Recent Progress on QoS Scheduling for Mobile Ad Hoc NetworksDimitris N. Kanellopoulos, University of Patras, Patras, Greece
ABSTRACT
Mobileadhocnetworks(MANETs)usealgorithmsthatscheduletransmissionsinafairandefficientmanner.Amultihopschedulerschedulestransmissionssothatthechannelutilizationismaximizedwhileguaranteeingthequalityofservice(QoS)forallnodes.QoS-basedschedulinginMANETsmustbeobtainedundertime-criticalconditionsasthesenetworkshaveseveralfeaturesthatproduceuniquequeuingdynamics.SchedulersinMANETstakeintoaccountvariousQoSparameterssuchasend-to-endpacketdelay,packetdeliveryratio,flowpriority,etc.Also,schedulinginMANETstakesmanyformssuchasdistributedpriority,fair,opportunistic,etc.ThisarticleprovidesasurveyofschedulingtechniquesforMANETsanddiscussestheadvantagesanddisadvantagesofeachcategory.
KEywORdSChannel Access Scheduling, Mobile Ad Hoc Network, Packet Scheduling, Quality of Service, Routing
INTROdUCTION
Nowadays,therearemanytypesofwirelessnetworkssuchasmobileorcellularnetworks,wirelesspersonal area networks, wireless local area networks, wireless metropolitan area networks, andwirelessadhocnetworksorMANETs.AMANETisawirelessadhocnetworkmadeupofradionodesorganizedinameshtopology.Inparticular,aMANETisagroupofautonomousnodesthatformadynamic,multihopradionetworkinadecentralizedway(Looetal.,2012).MANETsaredeployedmainlyinemergencysituationslikebattlefieldandnaturaldisasters(e.g.,fordetectionofearthquakesandfloods)asthereisnoneedtodeployanyinfrastructuretomakenodestocommunicatewitheachother.Nodesthemselvesimplementthenetworkmanagementinacooperativefashion.Suchcooperationrequiresdetectingroutesandforwardingdatapackets.Inadhocmode,allnodesparticipateinbothdataprocessingandroutingtasks.Thenetworkalsoreliesonthemultihoptypeofroutingforthedatatransmission,sincethedestinationnodeisoftenoutoftheradio-rangeofthesourcenode,andsomenodescanactasaroutertoforwarddata(Kanellopoulos,2017).RoutinginMANETscanbecategorizedas:(1)proactiveor(2)reactiverouting.Inproactive(oron-demand)routing protocols, all nodes periodically exchange routing information to maintain a consistent,updated,andcompletenetworkview.Eachnodeusestheexchangedinformationtocalculatethecoststowardsallpossibledestinations.Ontheotherhand,reactive(ortable-driven)routingdoesnot
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dependonperiodicexchangeofroutinginformationorroutecalculation.Whenarouteisrequired,thenodemuststartaroutediscoveryprocess.RoutingprotocolsinMANETScanalsobecategorizedas:topology-based;destination-based;neighborselection-based;andpartitioning-based(Kanellopoulos,2017).MANETscan“self-heal”,automaticallyre-routingaroundanodethathaslostpower.
Inmultihopnetworks,twomainproblemsexistrelatedwithhiddenandexposedterminals(Looetal.,2012).Aprimaryproblemoccurswhentwoormorenodessimultaneouslytransmittoacommondestinationnode.Asecondaryproblemoccurswhenanodereceivingatransmissionintendedforit,isinterferedwithbyanothertransmissionnotintendedforit.TheIEEE802.11DistributedCoordinationFunction(DCF)isthemostpopularmediumaccesscontrol(MAC)mechanismforadhocnetworks(Bianchi,2000).DCFusesthecarriersensemultipleaccesswithcollisionavoidance(CSMA/CA)schemeasamechanismtodealwithcollisions.Ittriestoscheduletransmissionsinafairandefficientmanner.However,DCFincreasesthemediumaccessdelayinproportiontotheloadonthenetwork.Ithasalsomanydrawbackssuchashighoverhead,highjitter,andlimitedQoScapabilities(Vergadosetal.,2012).Moreover,DCFsuffersfromthefairnessproblem,whichiscausedbytheexistenceofhiddenterminalsandexacerbatedbytheadoptedbinaryexponentialbackoffalgorithmtoresolvecontention(Xu&Saadawi,2001).Toachievefairandefficientschedulingoftransmissions,oneofthedominantsolutionsistheTimeDivisionMultipleAccess(TDMA)sinceitisasimpleMACschemeandcanprolongthedevices’lifetimebyallowingthemtotransmitonlyaportionofthetimeduringtheconversation.Therefore,severalTDMAschedulershavebeenproposed(Sgoraetal.,2015).InaTDMAsystem,timeisdividedintoframesthatconsistoftimeslots.Framelengthisthenumberoftimeslotsineachframe.Atimeslothasaunittimerequiredforapackettobetransmittedbetweenadjacentnodes.Whennodesareincloserange,collisionsmayoccur,andtheuseofTDMArequiresproperschedulingsuchastoavoidcollisions.TheBroadcastSchedulingProblem(BSP)(orTDMAmessageschedulingproblem)considershowtoassignatleastonetransmissionslotforallnodes,whileensuringcollisionavoidance.BSPisaNP-completeproblem(Ephremides&Truong,1990)anditssolutionaimsatthefollowing(Chenetal.,2006):
• Tominimizethetotalframelengthand/orincreasethenetworkcapacity;• Tomaximizethenumberofsimultaneoustransmissionsfromnon-interferingnodes;• Tominimizetheaveragepacketdelay.
Spatialchannelreusecansignificantlyimprovenetworkperformancefromtheresourceutilizationviewpoint.SpatialReuseTDMA(STDMA)allowsatimeslottobesharedbygeographicallyseparatedradiounitssuchasaminimuminterferencetobeobtained.STDMAcanbeusedinMANETstoachievebothhighcapacityanddelayguarantees(Gronkvist,2006).InMANET,QoSisstandardizedintermsofcapacity,reliability,linkquality,delays/jitters,andnetworkcost.MultimediaapplicationsoverMANETarebuiltuponnetworkservicesthatimposespecificQoSrequirementssuchashigherthroughput,boundedpacketdelay,andreductioninlossrate.EachflowofdatapacketsfromasourcetoadestinationnodeneedsprerequisiteresourcesinorderdesiredQoStoeachindividualflowtobeprovided(Zhang,1995).Whenanodereceivesmultiplemessageforwardingrequests,itservesoneofthemandstorestheothersinitsqueue.AnorderinwhichtheserequestswillbeservediscalledSchedule.SelectingthatparticularSchedulethatisestimatedtocreatetheoptimumperformanceisverycrucial.Amongthepacketsinthequeue,aScheduler(schedulingalgorithm)determineswhichpacketwillbeservednext.Allflowpacketsareinadataqueueinordertobetransmittedbasedontheavailabilityofthesharedbroadcastchannel.Thesizeofthequeuinglengthwillbehigh,ifthechannelstateisbusy.Duetohighdelay,queuingpacketsmayleadtohighdroprate.Ifthequeuinglengthexceeds(i.e.,bufferisfull)allthequeuedtypewillstarttodropthepackets.Whenthebufferisfull,differentdroppoliciescanbeusedfordataandcontrolpackets(Chun&Baker,2002).
SchedulerscanguaranteeQoSprovisioningbyreducingtheend-to-enddelayanddroprate.QoSschedulingmakesdecisionsabouttheassignmentofresourcesandservicestothenodesatacurrent
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time.Itcangiveorsnatchouttheresourcesfromaparticularnodesothatthenetworkperformancecanbeoptimized.Whentrafficloadishigh,anefficientandfairschedulercouldhaveasignificanteffectontheMANETperformance.Wirelessschedulersdiffersignificantlyfromtheirwirednetworkschedulers(Fattah&Leung,2002).Inamultihopwirednetwork,whenanodehasdatapacketsfortransmission,itneedstoworryaboutthepacketsinitsowntransmissionqueueonly.But,thisisnotthecasewithawirelessnode.Sincethechannelisbroadcastinnature,multiplenodescontendforthechannelsimultaneouslyresultingintransmissionerrors.Hence,anodemustalsobeawareofthenatureoftrafficatthosenodesinitslocality.SchedulersinMANETsconfronttwoproblems(SridharandMunChoonChan,2008):
• Todecidetheorderinwhichpacketswaitingfortransmissionatanynodemustbedispatched.AllschedulersinMANETsgivehighprioritytocontrolpacketsoverdatapackets.Schedulersdiffergenerallyofhowtheyassignprioritiesamongdataqueues(Chun&Baker,2002).ControlanddatapacketsaremaintainedinseparatequeuesinFirstIn-FirstOut(FIFO)order,whilethedrop-tailpolicyisusedasaqueuemanagementalgorithminallschedulersforbuffermanagement.Thedrop-tailpolicydropspacketsfromthetailofthequeue,whenchannelcapacityisfull;
• Todecidehowdifferentnodesshareachannelina“contentionregion.”TDMAschedulersaimtoprovidedelayandpacketdeliveryguarantees.
MANETsposethefollowingdesignchallenges:
• Problemsrelatedtohiddenandexposedterminals;• Constraints on resources: MANET devices work with limited CPU processing capabilities,
limitedbatterylife,limitedbandwidthsupport,limitedstorageetc.;• Error-pronesharedbroadcastchannel:Thetransmissionsbyanodearebroadcastinnature,and
MAClayeralgorithmstrytocontrolaccesstothesharedbroadcastchannel.Thewirelesslinkshavealsoahighererrorrate,fading,interferenceofsignalsetc.;
• Nodesmobility:ThedynamicnatureofMANETresultstofrequentlychangingtopologyandlinkbreaks.Itmakesroutingmoredifficultbecauseofthefrequentroutechange/routebreakleadingtolossofconnectivity.Newchallengesforvideotransmissionarealsoimposedasthemobilityofnodesaddsanextraoverhead(Kanellopoulos,2017).Theroutesmustbeupdatedfrequently.
The main difference in designing packet schedulers in MANETs is that not all nodes cancommunicate directly with each other and the network topology changes rapidly. Schedulers inMANETstakeintoaccountvariousQoSparameters:boundedpacketdelay,packetdeliveryratio(PDR),flowrate,loadofperflowqueues,fairness,remaininghopsanddistancetotraverseetc.QoSschedulingmustbeobtainedundertime-criticalconditionsasMANETshaveseveralfeaturesthatmayproduceuniquequeuingdynamics.Suchfeaturesare:(1)themultiplerolesofnodesasroutersandterminals;(2)themultihopforwardingofpackets;and(3)thenode’smobilitythatinducesfrequenttransmissionofroutepackets.
Chun and Baker (2002) examined the queuing dynamics at nodes and evaluated MANETperformanceunderdifferentpacketschedulersthatuseDynamicSourceRouting(DSR)andGreedyPerimeterStatelessRouting(GPSR)as theunderlyingroutingprotocols.Theyfoundthatsettingprioritiesamongdatapacketscandecreaseend-to-endpacketdelaysignificantly.Theyalsoshowedthatgivingprioritytocontrolpackets(overdatapackets)affectstheperformance,whenmobilityishigh.
Motivation for Surveying QoS Scheduling in MANETsFattahandLeung(2002)surveyedschedulingtechniquesforvarious typesofwirelessnetworks,especiallyforTDMAandCDMA.However,theygavelittleattentiontoschedulersforMANETs.In
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acode-divisionmultipleaccess(CDMA)network,severalnodesshareabandoffrequencies(Zanderetal.,2016).CDMAemploysspread-spectrumtechnologyandaspecialcodingscheme.Eachnodehasadifferentspreadingcode,andthustheinterferenceproblemcanbetoleratedtoacertaindegree.Twonodescantransmitinthesametimeslotwithoutmutualinterference,iftheyarelocatedmorethantwohopsapart.Enzaietal.(2010)presentedschedulingtechniquesdevelopedforMANETswithregardstotheirstrengthsandshortcomings.Annadurai(2011)presentedsomeschedulingtechniquesforMANETs,buthefocusedmainlyondesirablefeaturesanddesignchallengesofsuchschedulers.Sgoraetal.(2015)classifiedTDMAschedulersbasedonseveralfactors,suchastheentitythatisscheduled;thenetworktopologyinformationthatisneededtoproduceormaintaintheschedule;andtheentitythatperformsthecomputationthatproducesandmaintainstheschedules.Theyalsodiscussedtheadvantagesanddisadvantagesofeachcategory.Finally,Jiaoetal.(2016)reviewedninetypicalbackpressure-basedroutingandschedulingprotocolsforwirelessmultihopnetworks.
Tothebestofourknowledge,acomprehensivesurveyofschedulingforMANETsdoesnotexist,andistheaimofthispaper.Thecontributionsofthissurveypaperare:
• ToanalyzeQoS-basedschedulinginMANET;• TosurveytheexistingschedulingschemesinMANETs;• Todiscussfutureresearchareassuchascross-layerdesignschedulingforenergycontroland
fuzzy-basedscheduling.
Theremainderofthispaperisorganizedasfollows:ThesecondSectionenliststhewirelessscheduler’scomponentsandproperties.ThethirdSectiondiscussesvariousschedulingcategoriesforMANET.The fourthSectionconsiderscross-layerdesignschedulers,while the fifthSectionpresentsfuzzy-basedschedulers.Finally,thesixthSectionconcludesthepaperandgivesdirectionsforfurtherresearch.
SCHEdULER COMPONENTS ANd PROPERTIES
Ascheduler(Figure1)includesthefollowingcomponents(Fattah&Leung,2002):(1)anerror-freeservicemodelthatdescribeshowthealgorithmprovidesservicetoflowswitherror-freechannels;(2)a lead/lagcounterforeachflowthat indicateswhether theflowis leading, insynchwith,orlaggingitserrorfreeservicemodelandbyhowmuch;(3)acompensationmodelusedtoimprovefairnessamongflows.Alaggingflowiscompensatedattheexpenseofleadingflows,whenitslinkbecomeserror-freeagain;(4)separateslotandpacketqueuesforeachflowcanbeusedtosupportdelaysensitiveanderror-sensitiveflows.Whenapacketarrives,itistime-stampedandplacedinthepacketqueue;(5)ameansformonitoringandpredictingthechannelstateforeverybackloggedflow.
Awirelessschedulershouldpossessthefollowingproperties(Fattah&Leung,2002):
• Efficient link utilization:Theschedulershouldnotassignatransmissionslottoaflowwithacurrentlybadlink;
• Delay bound:Thealgorithmshouldprovidedelayboundguaranteesforindividualflows;• Fairness:Thealgorithmshoulddistributeavailableresourcesfairlyacrossflows;• Throughput:Thescheduler shouldprovideguaranteedshort-term throughput forerror-free
flowsandguaranteedlong-termthroughputforallflows;• Low complexity:Alow-complexityalgorithmispreferredasschedulingdecisionsinMANETs
havetobemadeveryrapidly(Guptaetal.,2009);• Graceful service degradation:Aflowthathasreceivedexcessserviceshouldexperiencea
smoothservicedegradationwhenrelinquishingtheexcessservicetolaggingflowswhoselinksarenowgood;
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• Isolation:Thealgorithmshouldisolateaflowfromtheilleffectsofmisbehavingflows;• Energy consumption:Thealgorithmshouldtakeintoaccounttheneedtoprolongthebattery
lifeofthemobiledevice.Toconserveenergy,anodemusttransmit/receiveincontiguoustimeslotsandthengointoasleep(verylowenergyconsumption)modeforanextendedperiodratherthan to rapidly switchamong transmit, receive, and sleepmodes.Thispreferencehas tobebalancedagainsttheneedtomaintainQoSlevels.Forexample,theSleepandawakescheduler(Prashanthinietal.,2016)enablesthechannelduringthedatatransmissiononly;
• Delay/bandwidth decoupling:Formultimediaapplications,thedelaymustbetightlycoupledwiththereservedrate;
• Scalability:Asthenumberofflowsincreases,thealgorithmshouldoperateefficiently;• Topology-transparency:Atopology-independentschedulerispreferredasitworksefficiently
regardlessofhowfrequentlyandunpredictablytheMANETtopologychanges;• Low connectivity information requirement:Aschedulershouldkeepthecommunicationof
networkconnectivityinformationtoaminimum,asthiscommunicationconsumesbandwidth.
SCHEdULERS IN MANETS
AllMANETschedulers use thepriority scheduling scheme,where control anddatapackets aremaintainedinseparatequeuesinFIFOorder,whilehighpriorityisassignedtocontrolpackets(Chun&Baker,2002).Itisimportanttoassignhighprioritytocontrolpackets(e.g.,routingpacketsRREQ,RREP,andRERR).Forexample,ahighprioritymustbeassignedtorouteerrormessages,becauseasuccessfultransmissionofarouteerror(RERR)packetcansavealargenumberofmisdirecteddatapacketscominglatersoon.MostMANETschedulersdiffermainlyofhowtheyassignprioritiesbetweendatapackets.Whenthebufferisfull,differentdroppoliciesareusedfordataandcontrolpackets.Iftheincomingpacketisadatapacket,thedatapacketisdropped.Iftheincomingpacketisacontrolpacket,thelastenqueueddatapacketisdropped.Ifqueuedpacketsarecontrolpackets,theincomingcontrolpacketisdropped(Chun&Baker,2002).
Figure2showsaschedulerthatservesdatapacketsinweightedroundrobinfashion.EachCi(i=1,…,n)representsadataflowthatcanbeidentifiedbyasourceanddestinationpair.Roundrobinschedulingmaintainsper-flowqueues,whileeachflowqueueisallowedtosendonepacketatatime.Differentweights(priorities)canbeassignedtodataflows.Aweightedroundrobinschedulercanbeusedasapriorityschedulerthatguaranteesthatallflows(serviceclasses)areservedaccordingtotheirpriorities.Datapacketsinthequeuesaretransmittedbasedontheprioritylevels.Priority
Figure 1. A wireless scheduler [adapted from (Fattah & Leung, 2002)]
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canbedefinedbyusingQoSparameterssuchasboundedend-to-endpacketdelay,remaininghopstotraverse,remainingdistance,etc.
distributed vs. Centralized SchedulingWirelesspacketschedulerscanbeclassifiedintotwogroups.
Centralized SchedulingAnodecoordinatesaccesstothechannelandgivespermissionstoeverynodethatwantstotransmit.Onewell-knowncentralizedschedulingschemeis theIEEE802.11PointCoordinationFunction(PCF)whereacoordinatingaccesspointperiodicallypollseachnodeinitscoverageareainordertograntthenodesaccesstothesharedchannel.Centralizedschedulersmaintainaglobalviewoftheentirenetwork,andQoSguaranteescanbeestablishedeasilyaslongasthenetworkisrelativelystatic.But,thisisnotthecasewithMANETs!CentralizedschedulinginMANETshasalsomanydrawbacks(Sgoraetal.,2015):
• Itmaintainstopologyinformationfortheentirenetworkandittakesalotofoverheadforthecontrollertogatherthisinformation;
• Inthepresenceofnodemobility,thistopologyinformationmayobsolete;• Everytimethetopologychanges,thisinformationmustbeforwardedtothescheduler.Thus,
centralizedalgorithmshavetheworstperformanceintermsoftimeoverhead;• Centralizedschedulingisalsocomputation-intensiveforthecontrollertogeneratetheschedules.
Distributed TDMA SchedulingThecomputationforcreatingandmaintainingtheschedulesisdistributedamongthenodes.Eachnodelistenstothechannelanddecideswhethertotransmitornot,basedonitsobservations.NodesmakeuseofcontrolpacketssuchasRequesttoSend(RTS)andCleartoSend(CTS).Whenanodehasapacketfortransmission,ittransmitsanRTSmessagefirst.Nodesinthevicinityofthetransmittingnodeonhearingthispacket,updatetheirNetworkAllocationVectors(NAVs).Similarupdatesaredone,whentheCTStransmittedbythereceivernodeisheardbytheneighbournodes.TheNAVatanodereflectsthestateofthechannelintheimmediatefuture,therebyguidingthenodeintakingadecisiononwhentotransmititsreadypacket.Thus,theinformationcarriedbytheRTSandCTSpacketshelpsinreducingcontentionforthechannel,andtherebyitaidsinbringingdownthenumber
Figure 2. Priority scheduler for data packets
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ofcollisionsinthechannel.Distributedalgorithmshaveagoodperformancebecauseslotassignmentsmaydependontheactualtrafficrequirements(Sgoraetal.,2015).
work-Conserving vs. Non-work-Conserving SchedulingSchedulerscanalsobeclassifiedasfollows(Zhang,1995):
• Awork-conservingschedulerisneveridle,ifthereisapacketawaitingfortransmission.Work-conservingschedulersareGeneralizedProcessorSharing(GPS),WeightedFairQueuing(WFQ),VirtualClock(VC),WeightedRound-Robin(WRR),Self-ClockedFairQueuing(SCFQ),andDeficitRound-Robin(DRR);
• Incontrast, anon-work-conserving schedulermaybe idle, even if there is abackloggedpacket in thenode,becauseitmaybeexpectinganotherhigher-prioritypacket toarrive.ExamplesareHierarchicalRound-Robin(HRR),Stop-and-GoQueuing(SGQ),andJitter-Earliest-Due-Date(Jitter-EDD).Non-work-conservingschedulershavehigheraveragepacketdelay than their work-conserving counterparts. They can be used in voice applications,wheredelay-jitterismoreimportantthandelay.Somenon-work-conservingschedulersareoriginallyproposedforwirednetworksandcanbeusedastheerror-freeservicemodelinthedesignofwirelessschedulers.
SchedulinginMANETstakesmanyforms(Figure3)suchas:Delayboundscheduling,Load-basedqueuescheduling,Distributedpriorityscheduling,Topology-transparentscheduling,FairandOpportunisticscheduling,etc.
Hereafter,wesummarizethemostimportanttypesofschedulinginMANETs.
Figure 3. Categories of scheduling in MANETs
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delay Bound SchedulingAkeyissueinwirelessnetworksishowtoassigndelaybudgetstoeachnetworknodealongtheroutingpathsothattheend-to-enddelayrequirementsofthecurrentapplicationsaremet.ZnatiandMelhem(2004)formalizedtheoptimalper-nodedelayassignmentproblem,whichtakesintoconsiderationtheworkloadacrosstheroutingpath.Theyproposedanoptimalalgorithmthatcomputesfeasibledelayvaluesfordifferentclassesofschedulingstrategies.Theiralgorithmcomputesasetoffeasibledelaysateachnodeforeachparticularflowandclassofdelay-basedservers.Thisoptimalalgorithmproduceshigherflowacceptanceratios.But,forlightly-loadednetworks,thecomputationalcomplexityofthisalgorithmmaynotbewarranted.Toovercomethisshortcoming,theauthorsproposedtwoheuristics,EPH()andLBH(),toapproximatetheoptimalstrategy.BothheuristicsperformcloselytotheoptimalschemesandwithsomelimitationstheycanbeusedinMANETs.
Wang and Ramanathan (2005) addressed the problem of concurrently providing end-to-endthroughputanddelayassurancesinwirelessadhocnetworks.TheyproposedtheDynamicClassSelection (DCS)algorithm,which isbasedonNeighborhoodProportionalDelayDifferentiation(NPDD)servicemodel(Wang&Ramanathan,2003).TheauthorsusedgametheoreticconceptstomodelDCSapplicationsinanNPDDnetworkasselfishplayersinanon-cooperativegame.WithNPDD,applicationsachievetheirdesiredend-to-endQoSbyusingdynamicclassselection(DCS)algorithms.TheyprovedthatthereisanequilibriumforsuchNPDDnetworks.
Akyildizetal.(2005)proposedaRateControlScheme(RCS)forreal-timeinteractiveapplicationsinnetworkswithhighbandwidth-delayproductsandhighbiterrorrates.SuiandShin(2005)evaluatedtheend-to-enddelayperformanceofaggregateschedulingwithGuaranteed-Rate(GR)algorithms.Deterministicend-to-enddelayboundsforasingleaggregationarederivedundertheassumptionthatallincomingflowsatanaggregatorconformtothetokenbucketmodel.ThreetypesofGRschedulingalgorithmscanbeusedbyanaggregator:(1)stand-aloneGR;(2)two-levelhierarchicalGR;and(3) rate-controlled two-levelhierarchicalGR.Byusing theGRschedulingalgorithms for trafficaggregates,theauthorsshowednotonlytheexistenceofdelayboundsforeachflow,butalsothefactthat,undercertainconditions(e.g.,whentheaggregatetraversesalongpathaftertheaggregationpoint),theboundsaresmallerthanthoseofper-flowscheduling.Aggregateschedulingisveryrobustandcanexploitstatisticalmultiplexinggains.Itperformsbetterthanper-flowschedulinginmostofthesimulationscenariostheyconsidered.AggregateschedulinginMANETsneedsfurtherconsideration.
Vaidhegietal.(2014)proposedadelay-sensitivepacketschedulertodeliverdelaysensitivedataoveramultihopnetwork.Basedonend-to-enddelayrequirements,packeturgency,nodeurgency,and routeurgencyare calculated.Basedon theseurgencymetrics, the schedulerdetermines thetransmissionorderofeachpackettominimizethenodeurgencywithoutunnecessarypacketdrop.Thejointroutingalgorithmestablishesaroutetominimizethederivativesofrouteurgencyinordertomaximizethenumberofpacketsdeliveredwithintherequiredend-to-enddelay.
BanerjeeandDutta(2014)proposedadelay-efficientenergyandvelocityconsciousnon-preemptive scheduler (DEV-NS scheduler). DEV-NS is concerned about the cost of route-rediscoveryduetolinkbreakage.Linkbreakagemaytakeplaceduetocompleteexhaustionofbatterypowerofanodeorwhenanodegoesoutoftheradio-rangeofoneofitsuplinkneighbourthatwasitspredecessorinthebrokenroute.DEV-NSinstructseachnodetoassignweightstoitsuplinkneighboursatregularintervals.
SharmaandKumar(2017)proposedanestimation-basedqueueschedulingmodelthathandleslargetrafficandensuresQoStoend-users.Theyprovedthatestimation-basedqueueschedulingcanadapt toanyhard real-timemultimediaapplicationoverMANET.The transmissionschemewasintegratedwithquaternion-basedKalmanFilter thatestimates thequeueselection,andperformstrafficpredictionanddelaysestimationswithhigheraccuracy.Finally,Kumar(2017)proposedanadaptivebroadcastschedulingalgorithmforMANETusingDSRprotocol.Theproposedschemeprovideslowend-to-enddelayandhighthroughput.
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Load-Based Queue SchedulingTheLoad-BasedQueueScheduling(LBQS)algorithm(Chenetal.,2006)caneffectivelydecreasethenetworktransmissiondelayinMANET.InLBQS,eachnodethoroughlytakesintoaccountitsownloadstate,whenforwardingpackets.Theprioritiesofpacketsareassignedaccordingtothecurrentnode’sloadlevel.ThreeloadlevelsaredefinedbyusingQueuelengthasloadindicator,andtwothresholds:MinthandMaxth.Inthelight-loadlevel,theQueuelengthislessthanMinth,whileinthemedium-loadleveltheQueuelengthisbetweenMinthandMaxth.Intheheavy-loadlevel,theQueuelengthisbiggerthanMaxth.Maxthshouldbesetmuchclosertothequeuesize:
• Light-load level:Schedulingprioritiesaregiventoallroutingmessages.Thenodecanprovideenough buffers to hold all the incoming packets. So, the node helps to complete the routediscoveryprocessquickly;
• Medium-load level:The forwardingdelayand loadachieveabalance,and thenodenearlyworksatitsstablestate.However,route-request(RREQ)androute-reply(RREP)controlpacketsaretreatedsimilarlyasdatapacketsinordertoavoidcongestion.GivingprioritytoRREQandRREProutingmessageswillcausemorepacketsrushingtothisnode,whichwillmakethenodeoverloaded.Routeerror(RERR)packetshavepriorityasinLight-loadlevel;
• Heavy-load level:ThebroadcastingofRREQmessagesinsearchofroutesinthenetworkisahighlyredundantprocessandthefloodingofRREQmessageswillfillupthebufferquickly.Therefore, thenodeshoulddelayorforbidtheconstructionofnewroutepassingthroughit,suchastoavoidnetworktransmissiondelayandpacketloss.Torecoverfromthisseverestate,allnewlyarrivingRREQmessagesaredropped.RREPmessagesthatcarryroutinginformationhavemuchlessredundancy,sothesamepriorityasdatapacketsisstillgiventothem.
GivinghighprioritytoRREQmessagescanassurethatthenewlyconstructedroutewillbetheshortest.However,theshortestpathmaybenotthebest,ifsomeintermediatenodeiscongested.Whenthequeuebufferisfull,itshouldnotbegivenpriorityforschedulingtoallroutingmessages.Otherwise,aRREQmessagemayberepliedalthoughthebufferhasbeenfullofpackets.AsuccessfultransmissionofanRREPwillconstructaroutingpaththroughthisnode,whichwillmakethenodemorecongested.RREQandRREPmessagesmustbedropped from the frontof thequeueuntilenoughroomisexposedfornewlyarrivingdatapackets(newlyarrivingRREQandRREPmustbedroppedfirst).Otherwise,datapacketsmustbedroppedfromthetail(Chenetal.,2006).AsuccessfultransmissionofaRERRmessagemusthavehighprioritybecause itcansavea largenumberofmisdirecteddatapacketscominglatersoon.
Whentheschedulerisoverloaded,theDominoeffectmayalsooccur:i.e.,thefirstpacketthatmissesitsdeadlinemaycauseallfollowingpacketstomisstheirdeadlines.Insuchasituation,EarliestDeadlineFirst(EDF)schedulingdoesnotprovideanyguaranteeforpacketstomeettheirdeadlines.AnEDFschedulerdetermines thepacket transmissionorderbyconsidering thearrival timeandend-to-enddelayrequirementofeachpacket.InEDF,apacketarrivingattimetandhavingdelaybounddhasadeadlinet+d.Basedonthisdeadline,thepacketsarescheduled.TodealwithEDFoverloads,manyheuristicEDFalgorithmshavebeenproposed(Lametal.,2004).TheFlexibleEDF(FEDF)scheduler(Dehbi&Mikou,2008)correctstheEDFdominoeffectinanearly-overloadedsystem.ItperformsbetterthanEDFbyenhancingQoSforsoftreal-timetrafficwithoutsignificantdegradationoflessconstrainedtraffic.
Vergadosetal.(2018)definedloadastheratioofthequeuelengthoverthenumberofallocatedslotsandproposedadistributednodescheduler(LocalVotingalgorithm).Theiralgorithmequalizestheloadthroughslotreallocation,basedonlocalinformationexchange.Localvotingalgorithmstemsfromthefindingthattheshortestdeliverytime(ordelay)isobtained,whentheloadisequalizedthroughoutthenetwork.WithLocalVoting,thenetworksystemconvergesasymptoticallytowards
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theoptimalscheduling.LocalVotingachievesbetterperformancethanotherdistributedalgorithms,intermsofaveragedelay,maximumdelay,andfairness.Despitebeingdistributed,theperformanceofLocalVotingisalsofoundtobeveryclosetoacentralizedalgorithmthatisdeemedtohavetheoptimalperformance.
distributed Priority SchedulingIntheDistributedPriorityScheduling(DPS)(Kanodiaetal.,2002),eachpackethasanassociatedpriorityindex,whichcanbecomputedwithpurelylocalinformation(e.g.,adeadline).DSPusestheprincipleofpiggybacking,wherepriorityindexofahead-of-line(HOL)packetisattachedtoexistingmessages.DPSalsomaintainstheschedulingtable,whichpointstotheprioritylevelofthenoderelativetoothernodes.EachnodelocallyconstructsaschedulingtablebasedonoverheardinformationandincorporatesitsestimateofitsrelativepriorityintoMAC.WhenanodeissuesaRequestToSend(RTS)inIEEE802.11,itpiggybacksthepriorityindexofitscurrentpacket.NodesthatoverhearthisRTSwillinsertanentryintoalocalschedulingtable.IfthenodeisgrantedaCTS,itincludesthepriorityindexofitshead-of-line(higherpriority)packetintheDATApacket,whichisalsoinsertedinthelocaltablebyoverhearingnodes.Then,eachnodecanassessthepriorityofitsownHOLpacketinrelationtoits(necessarilypartial)listofotherHOLpackets.Thisinformationcanbeexploitedviaaminormodificationofexisting802.11prioritizedback-offschemestocloselyapproximatea“global”dynamicpriorityscheduleinadistributedway.Theconceptofpriorityindexcanbeimplementedwithtrafficcontrolalgorithms,suchasVirtualClock(VC)(Zhang,1991).
In the MAC layer of MANETs, the distributed laxity-based priority scheduling scheme(Karthigeyanetal.,2005)(fortime-sensitivetraffic),selectsthepackettobetransmittednext,basedonaprioritycalculationfunctionthatconsiderstheuniformlaxitybudgetoftheflow,currentPDRoftheflow,andthedesiredPDR(PacketDeliveryRatio).
YangandVaidya(2006)proposedapriorityschedulingMACprotocolforadhocnetworks,namedBusyTonePriorityScheduling(BTPS).InBTPS,thetotalavailablechannelbandwidthisdividedintothreeparts:BT1channel,DatachannelandBT2channel,withrespectivebandwidthpercentageof1%,98%,and1%.TheresultingDatachannelhasabitrateof1.96Mbps.Withtheuseoftwonarrow-bandbusytonesignals,BTPSensureschannelaccessofhighprioritypackets.Intheabsenceofhighprioritypackets,lowpriorityflowscanmakefulluseofavailablebandwidthinBTPS.BTPSiseffectivewithrespectto“deliveryratioofhighprioritypackets”and“aggregatethroughput”.
SridharandMunChoonChan(2008)proposedachannelawareschedulingmechanismforMANETs(CaSMA)thattakesintoaccountboththecongestionstateandend-to-endpathduration.Theyrepresentedend-to-endchannelconditionasresiduallifetimeforchannel-awareness,andtheyincludedaqueuesizeparametertomaketheschedulingschemecongestion-aware.Duringthepathsetup,theestimatesofthepathlifetimesarecollectedandstored.Thispathlifetimevalue is used as a parameter to represent the end-to-end channel condition. During packetscheduling,CaSMAselectspacketswhichhaveahighprobabilityofreachingthedestination.CaSMAconsidersthecostofalinkbreakbygivingprioritytothoseflowsthathavealongernormalized(withpathresiduallifetime)backlogqueue.CaSMAreducestheaccumulationofpackets(backlogs)attheendofflowon-times.
Akyoletal.(2008)studiedtheproblemofjointlyperformingschedulingandcongestioncontrolinMANETssothatnetworkqueuesremainboundedandtheresultingflowratessatisfyanassociatednetworkutilitymaximizationproblem.Theoreticalsolutionstothisproblemarebasedoncombiningdifferential-backlogschedulingalgorithmswithutility-basedcongestioncontrol.Theauthorsdescribedawirelessgreedyprimal-dual(wGPD)algorithmforcombinedcongestioncontrolandschedulingthatsolvesthisproblem.TheydefinedaspecificnetworkutilitymaximizationproblemthatisappropriateforMANETs.TheyshowedhowthewGPDalgorithmanditsassociatedsignalingcanbeimplementedinpracticewithminimaldisruptiontoexistingwirelessprotocols.
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Topology-Transparent TdMA SchedulingBasedonwhetherthedetailednetworkconnectivityinformationisrequiredornot,schedulerscanbecategorizedas:
• Topology-dependentschedulersfindaminimumtotalframelength,conflict-freeschedule,basedonthedetailednetworktopology.Re-computationandinformationexchangesarerequiredtomaintainaccuratenetwork topology informationanddistribute thenewschedules,when thenetworktopologychanges(Chlamtac&Farago,1994).Therobustnessandeffectivenessofsuchschedulersareunderminedinlarge,highlydynamicMANETs;
• Topology-transparent schedulers are suitable for MANETs because they are independent ofnetworktopologyandhaveexcellentmobilitysupport(Chlamtac&Farago,1994;Ju&Li,1998;Caietal.,2003;Farnoud&Valaee,2009).Theyarealsofullydistributedandlesscomplexthanthetopology-dependentschedulers(Xuetal.,2011).Atopology-transparentTDMAschedulerallowseachnodetotransmitinanumberoftimeslotsineachframe.Thetimeswhennodeitransmitsinaframecorrespondtoauniquecodesuchthatforanygivenneighborkofnodei,nodeihasatleastonetransmissionslotduringwhichitsneighbornodekandnoneofksownneighborsaretransmitting.Withinanygiventimeframe,anyneighborofnodeicanreceiveatleastonecollision-freepacketfromnodei.Intopology-transparentschedulers,thelengthoftheschedulingcycleisverylong,andtheobtainedframelengthdependsonthenetworksize(Chengetal.,2013).Topology-transparentschedulersprovidelowQoSastheyassignslotstonodeswithouttakingintoaccounttrafficdemands.Theyconsumealotofbandwidthsincetheopportunityforspatialreuseisminimal.Thisleadstolowerthroughputandlargerdelaysthaninotheralgorithms.However, theyaremorereliable thanotherschedulersbecauseforeachnodeascheduleisalwaysimplemented,andnodefailureswillnotaffecttherestofthenetwork.Topologytransparentschedulershavethefollowinglimitations(Amouris,2005):◦ Thesenderisunabletoknowwhichneighbor(s)cancorrectlyreceivethepacketitsends
inaparticularslot;◦ Theefficiencyoftheschedulerdropsquadraticallyasthedensityofthenetworkincreases;◦ Theyarenotsuitable forMANETs thatcanexhibitsignificantvariance in theirdensity
and/orsize.
Thefirsttopology-transparentbroadcastTDMAscheduler(Chlamtac&Farago,1994)usesthemathematicalpropertiesofGaloisfields.Thisalgorithmassignstoeachnodeauniquepolynomialfunctionthatguaranteesthatatleastonetimeslotinaframewouldbecollision-free.Theperformanceofthisalgorithmdependsonlyonthenumberofnodesinthenetworkandthemaximumdegree(i.e.,thenumberofneighborsthateachnodecanhave).Themaximumnumberoftransmissionisoneinaframe,andthusthethroughputobtainedbythisalgorithmisrelativelysmall(Liuetal.,2012).Caietal.(2003)proposedtwotopology-transparentTDMAalgorithms.TheirfirstalgorithmfocusesonsinglechannelnetworksandisbasedontheGaloisfieldtheoryandtheLatinsquaretheory,whiletheirsecondonefocusesonmultichannelnetworks.Bothalgorithmsoutperformthealgorithmproposedin(Chlamtac&Farago,1994)intermsofachievingtheminimumtotalframelength.Additionally,theuseofLatinsquaresachievesabetterpotentialperformancegaincomparedwiththeonlyuseofthemodifiedGaloisfielddesign(MGD)algorithm.
Based on the theory of block designs, Su et al. (2004) proposed two topology-transparentbroadcastTDMAschedulers foradhocnetworks.Theyconsidered timeslotsas“treatments”oftheBalancedIncompleteBlock(BIB)design,andthesetofnodeactivationtimesoftheschedulingproblemasblocks.Bothschedulersaimtomaximizetheminimumnumberofcommontreatmentsbetweeneverypairofblocks.
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OikonomouandStavrakakis(2004)insertedaninterestingprobabilisticpolicythatincreasessystemthroughputintotopology-transparentalgorithms.Theprobabilisticpolicyallowsaspecificnodeunotonlytoaccessthesetoftimeslotsthatitisallowedtotransmitbutalsoothertimeslots(outsidetheset)thatdonotbelongtonodeu,withprobabilityp(Chen&Jiang,2006).
Thestealing-TDMAalgorithm(sTDMA)(Chen&Jiang,2006)usesanACKmechanismtoreserve time slots for solving collision problems. sTDMA achieves better performance in termsof collision probability and power consumption in comparison with the algorithm proposed in(Oikonomou&Stavrakakis,2004).
JuandLi(2006)improvedthealgorithmproposedbyChlamtacandFarago(1994)inordertomaximizeminimumthroughput.Intheiralgorithm,thescheduleisgeneratedbyapplyingcodetheory;byusingtheHammingweightandHammingdistancetodescribetherelationshipbetweenthetransmissionslotassignmentsoftwonodes.Theiralgorithmoutperformsthealgorithmin(Chlamtac&Farago,1994)intermsoftheminimumguaranteedthroughputunderanytrafficconditionsandminimumdelay(whenthesystemisunderverylighttraffic)andmaximumdelay(whenthesystemisunderveryheavytraffic)times.
Based on coding theory, Sun et al. (2008) proposed a topology-transparent algorithm formulticastandbroadcastcommunicationsforwirelessmultihopnetworks.InsteadofminimizingtheTDMAframelength,theiralgorithmmaximizestheminimumexpectedthroughput.TheauthorsusedtheTimeSlotAllocationFunction(TSAF)tocalculatethepositionofaselectedtransmissionslotinaframeforeachnode.Then,basedonthenumberofeachnode’stransmissionopportunitiesineachframe,aswellasthehighestdegreeamongallTSAFs,theminimumexpectednumberofsuccessfultransmissionsperframewascomputedforbothmulticastingandbroadcasting.TheperformanceoftheiralgorithmisbetterthanconventionalTDMAintermsofexpecteddelayandminimumexpectedthroughput.
Rheeetal.(2009)proposedadistributedTDMAschedulingalgorithm(DRAND)thatensuresthecollisionavoidanceofeachtwo-hopneighbor.DRANDisadistributedTDMAschedulerthatensuresthecollisionavoidanceofeachtwo-hopneighbor.DRANDalgorithmcansuccessfullyadapttolocaltopologychanges.Itdoesnotrequiresynchronizationatanytime,butrunningandmessagecomplexitydependsonthenumberofanode’stwo-hopneighbors.DRANDisperfectforwirelessnetworkswithlimitedmobility,andthusitisnotanefficientsolutionforMANETs.
Liu et al. (2012) introduced a distributed topology-transparent scheduler for multicastandbroadcastcommunicationsinMANETs.Thedesignoftheirschedulerisbasedoncodingtheory.Theirschedulerguaranteesthattheprobabilityofamulticastorbroadcasttransmissionsucceeding within a frame time exceeds a given threshold. Their scheduler obtains betterperformanceintermsofthroughputincomparisonwiththealgorithms,proposedin(Chlamtac&Farago,1994;Sunetal.,2008).
Recently,Liuetal.(2014)proposedatopology-transparentschedulerforMANETnodesthathavethemultiplepacketreception(MPR)capabilityofdecodingmorethanonepacket,simultaneously,whenconcurrenttransmissionsoccur.MANETdevicesobtainedthepowerfulMPRcapabilityduetotherecentadvancesinthePhysicallayer.TheinteractionbetweentheMPRPhysical layerand theMAClayer isunderconsideration,while some randomaccessMACprotocolshavebeenproposedtoimprovethenetworkperformancebyexploitingthispowerfulMPRcapability.Theproposedtopology-transparentscheduler(m,l)-TTS(Liuetal.,2014)takesfulladvantageoftheMPRcapabilitytoimprovethenetworkperformance.Ittakesalsointoaccount:(1)themaximumnumberofconcurrenttransmissionsbeingdecoded(m);and(2) thenumberofcodesassignedtoeachuser(l).Theimprovementof theiralgorithmover the conventional topology-transparent schedulers (with the collision-based receptionmodel)islinearwithm.
Table1comparestopology-transparentschedulers.
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Cluster-Based Multi-Channel SchedulingTheTwo-TierSlotAllocationProtocol(2TSAP)(Chaoetal.,2002)hasacluster-basedmechanism.Eachclusterofnodeshasascheduler(ormaster).Clustersmaybeoverlapped,eachwithadesignatedcode.Theclustercanbeformedasfollows.Eachnodeperiodicallybroadcastsbeacons.Basedonthereceivedbeacons,nodeslearntheirneighbors,andrelatedinformation,suchasNodeID,Nodestability.Accordingtotheselectedcriterion,eachclustercandetermineitsscheduler.Toreceivetheservice,eachnodemustjoinaclusterandregisterwiththescheduler.Eachschedulerperiodically
Table 1. A comparison of topology-transparent schedulers
Scheme Features Comments
Chlamtac&Farago(1994)
Itsperformancedependsonlyonthenumberofnodesinthenetworkandthemaximumdegree.
Lowthroughput.Theoptimalminimumthroughputissensitivetoinaccuraciesintheestimateddesignvaluesofthenumberofnodesandthemaximumdegreeinthenetwork.
(Caietal.,2003)
Itisapplicableformulti-channelnetworks. Eachnodetransmitsthesamepacketinallofitsassignedslots.
(Suetal,2004)Considersnodemobility;maximizestheminimumsystemthroughput.
Anexhaustivesearchmethodtofindtheoptimalsolutionisrequired.
(Oikonomou&Stavrakakis,2004)
Increasedthroughput.Nomechanismisdeterminedforchoosingthenon-assignedslotstotransmitwithprobabilityp.Doesnoteliminatecollisions.
(Chen&Jiang,2006)
Reducespowerconsumptionanddecreasescollisionprobability.
IncreasedoverheadduetoACKs.
(Ju&Li,2006)
Thealgorithm’sperformancedependsonthenumberofnodesinthenetworkandthemaximumdegree.
Theoptimalminimumthroughputissensitivetoinaccuraciesintheestimateddesignvaluesofthenumberofnodesandthemaximumdegreeinthenetwork.
(Sunetal.,2008)
Maximizestheminimumexpectedthroughput.Considersmulticastingandbroadcasting.
NotsuitableforhighlydynamicMANETs.Doesnoteliminatecollisions.
(Rheeetal.,2009)
DRANDdoesnotacquireanysynchronizationatanytime.Canbeeffectivelyadaptedtolocaltopologychanges.
Therunningtimeandmessagecomplexityaresubjecttothenumberoftwo-hopneighborsofanode.Schedulescannotbechangedorrepaired.
(Xuetal.,2011)
Maximizestheguaranteedthroughput Requirestimesynchronization.
(Liuetal.,2012)
Considersmulticastingandbroadcasting.Guaranteesonesuccessfultransmissionexceedingagivenprobabilityandachievesamuchbetteraveragethroughput.
Notsuitablefordensenetworks.
(Liuetal,2014)
(m,l)-TTSusestheMPRcapabilitytoimprovethenetworkperformance
Itsimprovementoverotherconventionaltopology-transp.schedulersarelinearwiththemaximumnumberofconcurrenttransmissionsbeingdecoded.
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advertises itself as the scheduler to its cluster, fromwhichnewly arrivingnodes learnwhere toregister.Clustercommunicationsareclassifiedintointra-clusterandinter-clustercommunications:
• Intheintra-clustercommunication,packettransmissionofeachclustermemberisprocessedwithin itscluster.Eachclustermemberhasapacket toa randomdestination. If itspacketdestinationislocatedwithinthesamecluster,ittransmitsthepackettothedestinationdirectly(i.e.,directlink).Otherwise,itforwardsthepackettoitsownclusterheadinordertosavebatteryenergy(i.e.,uplink);
• In the inter-cluster communication, each cluster head broadcasts packets received from itsmembers to theirdestinationover specific channelsof theirdestination similar tobroadcastschedulingmethods(Zhengetal.,2005).
ToguaranteetheQoSandhighthroughput,TDMAisadaptedforclustercommunicationsbyallocatingafixedtimeslotperpackettoeachnodeovermultiplechannels.Theobjectiveofcluster-basedmulti-channelschedulersistomaximizetheend-to-endthroughputbyoptimizingthenumberoftotalTDMAslotsintheclustercommunications.Leeetal.(2007)proposedtheintra-clusterandtheinter-clusterschedulersforadhocnetworks.Variousuplinksanddirectlinksofclustersweretakenintoaccountforsplittingtrafficdemandsovermultiplechannelsintheintra-clusterschedulingalgorithm.Theinter-clusterschedulingalgorithmconsideredthesimultaneoustransmissionofclusterheadsandreceptionofclustermemberstoallocatetheadditionalchannelstotheproperclusters,basedontheinter-clustertrafficdemandmatrix.TheiralgorithmsminimizethenumberofTDMAslotsbysplittingtheslotsovertheadditionalchannelsandmaximizetheend-to-endthroughput.
Fair SchedulingWirelessfairschedulershideshortburstsoflocation-dependentchannelerrorsfromwell-behavedflows.Thisisachievedbydynamicallyswappingchannelallocationsbetweenbackloggedflowsthatperceivechannelerrorsandbackloggedflowsthatdonot.Thisswappingisdonewiththeintentionofreclaimingthechannelaccessfortheformer,whenitreceivesacleanchannel.Therefore,laggingflowsreceivecompensationfromleadingflows.Wirelessfairschedulersdefinehowtheswappingoccursandhowthecompensationmodelworks.AnapproachtoenhancefairnessinMANETsistouseDistributedFairQueueingScheduling.DistributedFairQueueinginMANETsischallengingbecause:(1)thewirelesschannelissharedamongmultiplecontendingnodesinaspatiallocality;(2)location-dependentchannelcontentioncomplicatesthefairnessnotion;and(3)thesenderofaflowdoesnothaveexplicitinformationregardingthecontendingflowsoriginatedfromothernodes.
Manyproposalsemulatefairqueueingoperations(i.e.,assignstartandfinishtagsforeachpacket)inadistributedmannerbyexploitingthebroadcastnatureofawirelesschannel.FairschedulinginMANETscanbedeployedintwoways:
• Timestamp-based queueing: A time-stamped scheduler serves packets according to theirtimestampvalues.Ineachdatapacket,twotimestamps(astarttagandafinishtag)havebeentagged-insertedaccordingtotheStart-timeFairQueueing(SFQ)algorithm(Goyaletal.,1997).Theservicetagforapacketcanbeeitherthestarttagorthefinishtag.Thepacketwiththesmallestservicetagwillbesentfirst;
• Credit-based queueing:Eachflowhasanunused“credit”thatisaccumulatedforfutureuse.Theflowwiththesmallestexcessvaluehastheprioritytotransmit,wherethe:
Excess_value = usage_value – credit(Chao&Liao,2003)
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Rukmani and Ganesan (2013) compared various queuing algorithms: FIFO (Fraser, 1985),PriorityQueuingAlgorithm(PQA)(Semeria,2001),WeightedFairQueuing(WFQ)(Semeria,2001),Class-BasedWeightedFairQueuing(CBWFQ),andLowLatencyQueuing(LLQ)algorithm.TheyobservedthatLLQperformsbestwiththereal-timetraffic(voiceandvideo)inMANET.LLQgivesminimumdelayandmaximumthroughputincomparisontootherqueuingalgorithms.
TheWFQalgorithmallocatesthebandwidthinproportiontotheweightsofthepacketflowssharingthechannel.Itprovidesadynamicfairqueuebydividingtheresourcesofthetrafficbasedontheweightsofthepackets.VaraprasadandWahidabanu(2011)proposedanalgorithmthatusesaWQFmodeltoallocatethebandwidthandstreamsynchronizationforsensitiveapplicationsthathavebursttrafficcharacteristics.Withtheirmethodthepacketsaretransmittedwiththeminimumdelayatthehighload.
TheExtendedHybridAsynchronousTimeDivisionMultipleAccess(EHATDMA)protocoldealswiththeunfairnesscausedby:thelackofsynchronizationproblem;thedoublecontentionareasproblem;andthelackofcoordinationproblem(He&Pung,2005).
Afairandmaximumbandwidthallocationcanpotentiallybe inconflict inaMANET.Luoet al. (2000)proposedamodel that addresses this conflict inmultihopwirelessnetworks.Theyimplementedanidealcentralizedpacketschedulerthatprovidesaminimum“fair”allocationofthechannelbandwidthforeachpacketflowandmaximizesspatialreuseofbandwidth.Theiralgorithmcanbecharacterizedastheminimum-degreegreedyalgorithm.
Nandagopaletal.(2000)proposedamechanismthatcantranslateanygivenfairnessrequirementinto a matching contention resolution algorithm. Jun and Sichitiu (2003) showed that per-flowqueueingattheNetworklayercanensurefairnessinwirelessmultihopnetworksattheexpenseofbandwidthefficiency.Theauthorsshowedthatper-flowqueuesattheNetworklayerwithMAC-layerQoSsupportmayprovidedifferentiatedservicesinwirelessmultihopnetworks.
Luoetal.(2004)proposedafairqueueingscheme(Maximize-Local-MinimumFairQueueing-MLM-FQ), inwhichlocalschedulersself-coordinatetheirschedulingdecisionsandcollectivelyachieve fair bandwidth sharing.Theyproposed theEnhancedMLM-FQ (EMLM-FQ) to furtherimprovethespatialchannelreuseandlimittheimpactofinaccurateschedulinginformationresultedfromcollisions.EMLM-FQachievesstatisticalshort-termthroughputanddelayboundsoverthesharedwirelesschannel.Analysisandextensivesimulationsconfirmedtheeffectivenessandefficiencyoftheirself-coordinatinglocalizeddesigninprovidingglobalfairchannelaccessinwirelessad-hocnetworks.
ChaoandLiao(2005)proposedtheTimestamp-BasedCompensationProtocol(TBCP)thatisproperforMANETs.TBCPadoptstheStart-timeFairQueueing(SFQ)asitsschedulingdisciplineandselectsthestarttagasitsservicetag.InTBCP,thetransmissionorderofapacketisdeterminedbytheservicetagofthepacket,thenumberofslotsperframeaflowcanuse,andflow’sQ-size.Then,eachnodeexchangestheinformationaboutthetransmissionorderofpacketswithitsneighbours.Thus,eachnodeknowstheservicetagsofothernodesandalsolearnswhenitwilltransmitpackets.Eachnodekeepsmonitoringitschannelstate.Whenthechanneliserror-prone,thenodestopsexchangingtransmissionmessageswithitsneighbours.Oncethechannelrecovers,theerror-pronenoderesumestheexchanges.Ifthisnodehaspacketswithservicetagssmallerthanitsneighboursafterrecovery,thesepacketsstillhavehigherprioritytobetransmitted.MultihopflowsarealsohandledbyTBCPwithintroducinganewparameter,calledQ-size.
IntheMaxMinFairSchedulingscheme(Tassiulas&Sarkar,2005),everysession(flow)alwayshasapackettotransmit.Eachnodeallocatesservicetokenstothesessionstraversingthenodeinaround-robin-likefashion.Theweightofanedgeinthetopologygraphinaslotistheminimumofthenumberoftokensofthecorrespondingsessionatthesession’ssourceanddestination.Ineachslot,thesessionsthatconstituteamaximumweightedmatchinginthetopologygrapharescheduledforservice.Wheneverasessionisserved,atokenisremovedfrombothitssourceanddestination.Vaidyaetal.(2005)proposedafullydistributedalgorithmforfairschedulinginawirelessLAN.Theiralgorithmensuresthatallpacketswillgetaproperbandwidthofthewirelesschannel.Their
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algorithmisderivedfromtheDCFintheIEEE802.11standard.Itschedulestransmissionssuchthatthebandwidthallocatedtodifferentflowsisproportionaltotheirweights.
The joint TDMA scheduling/load balancing algorithm (LB-FFVSA) for wireless multihopnetworksdeterminestheoptimalslotassignmentintermsofoverallperformanceandfairnessperflow(Vergadosetal.,2012).Thisisachievedthroughthecombinationofaschedulerthatassignstheappropriatetransmissionslotstoeachnodeandaloadbalancingtechniquethatimprovestheschedulingperformance by limiting the required frame length. LB-FFVSA exhibits improved performancecomparedtootherTDMAschedulersintermsoffairnessandthroughput.
weighted-Hop and weighted-distance SchedulingInmultihopwirelessnetworks,schedulingalgorithmscanassignhigherweights(priorities)todatapacketswithsmallernumbersofhopsorshortergeographicdistancestotheirdestinations.Suchalgorithmscanreducetheaveragedelaysignificantlyandimprovetheaveragethroughput(Chun&Baker,2002).Thedistancebetweenthesourceandthedestinationismeasuredusuallybythenumberofhops.
InShortestHop-LengthFirst(SHLF)scheduling,thedistanceinfluencesthetimeapackettakestoreachthedestination(Kakaraparthietal.,2000).SHLFrequiresthateachpacketcarriesthetotalnumberofhopstothedestination.SHLFalsobelongstotheclassofHead-of-Linequeuingalgorithmsandresultsindecreasingend-to-endpacketdelayofthenetwork.Theschedulingdecisionismadeateachnodeindependently,anditisbasedonthenumberofhops.
InLongestHop-LengthFirst(LHLF)scheduling,themetricusedisthenumberofhopsthepacketrequirestoreachitsdestination(Kakaraparthietal,2000).Packetshavingtotraverseoveralongnumberofhopswillhavealongend-to-enddelayandtransmissiondelay.Toreducethesedelays,LHLFschemeassignsahigherprioritytopacketsthathavetotraveloveralargernumberofhops.
Weighted-Hop SchedulingTheheaderof adatapacket carries a complete list ofnodes throughwhich thepacket shouldtravel. Thus, it includes the information about ‘remaining hops to traverse’ for this packet. Inroutingprotocols (exceptDSR), this information isobtained from the routing table that storesthe remaininghops todestinations.Theweighted-hopschedulingassumes that thepacket thatneedsfewerhopstotraverseispossibletoreachitsdestinationquicklyandincurslessqueuinginthenetwork(Kakaraparthietal.,2000).Weighted-hopschedulingassignsahigherprioritytodatapacketsthathavefewerremaininghopstotraverse.Itsortsdatapacketsinproportiontotheremaininghopstotraverseandshapesclassifieddataqueues(flows).Letusexplainhowitworks.Eachdataqueueisallowedtosendonepacketatatimeinaround-robinfashion.ThedataqueueoftheclassCikeepsdatapacketswhosenumberofremaininghopstotraverseisi.Ifthenumberofremaininghopsofadatapacketisgreaterthann(thenumberofdataqueues),thedatapacketisclassifiedintheclassCn.Afterthat,weassignweightstodataqueues.ThedataqueueoftheclassCireceivesweightWi(1≤i≤n).Aweightedroundrobinschedulercanguaranteethatpacketshavingfewerremaininghopstotraversewillreachfirst.
LiandKnightly(2002)definedaframeworkfordesignandanalysisofCoordinatedMultihopScheduling(CMS)whichexploitsinter-nodecoordination.InCMS,thetransmissionpriorityofapacketateachnodeisrecursivelyexpressedusingthetransmissionpriorityofthesamepacketatthepreviousnodealong the route.Thepacketschedulingalgorithmdetermines the transmissionpriorityofeachpacket,basedonthepacketurgency.TheauthorsillustratedthatCMSschedulerscanlimittrafficdistortiontowithinanarrowrangeresultinginimprovedend-to-endperformanceandmoreefficientresourceutilization.Theirtechniqueexploitsstatisticalresourcesharingamongflows,classes,andnodes.Theirresultsprovidethefirststatisticalmulti-nodemulticlassadmissioncontrolalgorithmfornetworksofworkconservingservers.
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Weighted-Distance SchedulingItgiveshigherweight todatapacketswhichhaveshortergeographicdistances.Theremainingdistanceisthedistancebetweenachosennexthopandadestination.UsingphysicaldistanceisauniquefeatureofMANETs.Nodesthatarecloseinthephysicaldistancearelikelytobecloseinthenetworktopology.Astheremainingphysicaldistancetoadestinationdecreases,theremaininghopstoadestinationinthenetworktopologyarelikelytodecrease.Theweighted-distanceschedulerisalsoaweightedroundrobinscheduler.Itgiveshigherweighttodatapacketsthathaveshorterremaining geographic distances to the destinations. The RemainingDistance is defined as thedistancebetweenachosennexthopnodeandadestination.EachclassCiisdeterminedbytheVirtualHop(Chun&Baker,2002):
VirtualHopRemainingDistance
QuantizationDistance�=
+11 (1)
whereQuantizationDistanceisthedistanceformappingthephysicaldistanceintotheclass.WhentheVirtualHopofadatapacketisgreaterthann,thispacketisclassifiedasCn.ThedataqueueoftheclassCnreceivesweightWi(1≤i≤n).Thehigherweightisassignedtothelowerclass.
LiangandDong(2007)addressedtheproblemofoptimizingthepackettransmissionscheduleinamultihopwirelessnetwork.Theydeterminedtheproperrelativeweightsassignedtotheremainingdistanceand the remaining lifetime inorder to rank theurgencyofapacket.Theyproposed theMultihopLatency-Aware(MLA)schedulerandaframework,basedonrecursivenon-homogeneousMarkoviananalysis,tostudytheeffectofthelifetime-distancefactoronpacketlossprobabilitywithdifferentconfigurationsofpeer-nodechannelcontention.Theydemonstratedquantitativelyhowtheproperbalancebetweendistanceandlifetimeinatransmissionschedulecansignificantlyimprovethenetworkperformance,evenunderimperfectscheduleimplementation.
Opportunistic SchedulingTheIEEE802.11wirelessmediaaccessstandardsupportsmultipledataratesatthePhysicallayer.Auto-rateadaptationmechanisms(Sadeghietal.,2002;Wangetal.,2004a)attheMAClayerutilizethismulti-ratecapabilitybyautomaticallyadaptingthetransmissionratetobestmatchthechannelconditions.Opportunisticschedulingtakesadvantageofthetime-varyingchannelamongdifferentreceiverstoimprovesystemperformance.
TheOpportunisticAutoRate(OAR)(Sadeghietal.,2002)protocolexploitsdurationsofhigh-qualitychannelsconditionsasitutilizesthemulti-ratecapabilityofIEEE802.11.OARprotocolopportunisticallysendsmultipleback-to-backdatapackets,wheneverthechannelqualityisgood.Aschannelcoherence times typicallyexceedmultiplepacket transmission timesforbothmobileandnon-mobileusers,OARachievessignificantthroughputgainsascomparedtopreviousauto-rateadaptationmechanisms.Moreover,overlongertimescales,OARensuresthatallnodesaregrantedchannel access for the same time-shares as achieved by single-rate IEEE 802.11. Sadeghi et al.(2002)describedmechanismstoimplementOARontopofanyexistingauto-rateadaptationschemeinanearlyIEEE802.11compliantmanner.TheyalsostudiedOARandcharacterizedthegainsinthroughputasafunctionofthechannelconditions.
Wang et al. (2004a) presented theOpportunistic packetScheduling andAutoRate (OSAR)protocolthatexploitsthechannelvariations.ThebasicideaofOSARisasfollows:ratherthanjustmatchingthechannelconditionforanodepairincommunications,OSARtakesadvantageofthemulti-userdiversityasmuchaspossibleandadapttherateaccordingly,i.e.,basedonthechannelconditionstoitsneighbouringnodes,thesenderchoosestheneighbouringnodewithchannelqualitybetterthancertainleveltoschedulethetransmissionsofpacketsinitsqueue,thentheoverallsystem
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throughputmaybeincreased.ThekeymechanismsofOSARarechannelawaremediaaccess,rateadaptation,andpacketbursting.
Wangetal.(2004b)introducedtheOpportunisticpacketSchedulingandMediaAccesscontrol(OSMA)protocoltoexploithigh-qualitychannelconditionundercertainfairnessconstraints.TheybasedtheirdesignonCSMA/CAsothatitcanbeincorporatedintothe802.11standard.ThekeymechanismsofOSMAprotocolare:multicastRTSandpriority-basedCTS.IntheOSMAprotocol,RTSincludesalistofcandidatereceivers.Amongthosewhoarequalifiedtoreceivedata,theonewiththehighestorderwouldbegrantedtocatchthechannelbyreplyingCTSinthefirstplace.TheorderinglistisupdateddynamicallyaccordingtocertainschedulingpolicysuchasRoundRobin(RR)andEarliertimestampFirst(ETF),andalsootherperformancemetrics,ex.,fairness,andtimeliness,canbeenhanced.OSMAexploitsthemultiuserdiversityintheCSMA/CAbasedwirelessnetworksandcanimprovethenetworkthroughputsignificantly.PatilandViciana(2007)proposedaclassofopportunisticschedulingdisciplines(OSD),whichhandlemixesofreal-timeandbest-effortflowsatawirelessaccesspoint.Theirdisciplinessupportprobabilisticservicerateguaranteestoreal-timeflows,whilestillachievingopportunisticthroughputgainsacrossusersandtraffictypes.
TheDistributedOpportunisticScheduling(DOS)foranad-hocnetworkinvolvesaprocessofjointchannelprobinganddistributedscheduling(Zhengetal.,2007).Duetochannelfading,thelinkconditioncorrespondingtoasuccessfulchannelprobingcouldbeeithergoodorpoor.Inthelattercase,furtherchannelprobing,althoughatthecostofadditionaldelay,mayleadtobetterchannelconditionsandhenceyieldhigher throughput.Thedesired tradeoff boils down to judiciously choosing theoptimalstoppingruleforchannelprobinganddistributedscheduling(anoptimalstoppingapproach).
InMANET,eachtransmitteroftenschedulesthetransmissionsindependently.However,duetoco-channelinterference,thedecisionsofneighbouringtransmittersarehighlycorrelated.ToachievetheQoSrequirements,nodesmustbecooperativetosharethecommonwirelesschannel.Chenetal.(2008)formulatedtheopportunisticschedulingproblembytakingintoaccounttheinteractionamongtheneighbouringtransmitters.TheyproposedtheCooperativeandOpportunisticScheduling(COS);adistributedoptimalschedulingpolicythatmaximizestheoverallnetworkperformance,whilesatisfyingQoSofindividualflows.InCOS,theIEEE802.11protocolismodifiedtoimplementtheoptimalschedulingpolicy.
Kimetal.(2013)proposedurgency-basedpacketschedulingandroutingalgorithmstoeffectivelydeliverdelay-sensitivedataoveramultihopMANETssupportingIEEE802.11multi-rateservice.Packeturgency,nodeurgency,androuteurgencyaredefinedonthebasisoftheend-to-enddelayrequirement.BasedontheseurgencymetricsandtheestimatedtransmissiondelayofeachpacketbyKalmanfilter,theurgency-basedpacketschedulerdeterminesthetransmissionorderanddroppolicytominimizethenodeurgencywithoutunnecessarypacketdrop.Theroutingalgorithmestablishesaroutetominimizethederivativeofrouteurgencyinordertomaximizethenumberofpacketsdeliveredwithintherequiredend-to-enddelay.Table2showsacomparisonofopportunisticschedulers.
Scheduling in Multipath RoutingMultipathroutingconsistsoffindingmultipleroutesbetweenasourceandadestinationnode.Itdistributestrafficonmultiplepathsbetweenthesource-destinationpair.ThesepathscanbeusedtocompensateforthedynamicnatureofMANET.Multipathroutingprotocolsformultihopnetworkscanbeclassifiedasproactive, reactive,orhybrid.PeriyasamyandKarthikeyan (2013) analyzedmultipathroutingprotocolsforMANETs.Theyarguedthattheperformanceofmultipathroutingisaffectedbytrafficassignmentandpacketscheduling.
GuoandKuo(2007)proposedtwopacketschedulingschemesbytakingintoaccountthemultipathroutingfeature.Theseschemesaretheuniformroundscheduling(URS)andthenon-uniformroundscheduling (NURS).Theyassumed that theend-to-enddelaybetweennodes follows thenormaldistribution.Theyalsomodelledeachpathasamultiple-nodeM/M/1tandemnetwork.M/M/1refers
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tothenegativeexponentialarrivalsandservicetimewithasingleserver.M/M/1queuingisthemostpopularsystemusedtoanalyzevariousschedulingschemes.GuoandKuo(2007)showedthatURSschemeoutperformstheNURS.
Obaidatetal.(2013)proposedtheQoS-awareMultipathRoutingProtocol(QMRP)thatreducesthedelayinordertoimprovethereliabilityandQoSofthemultimediacommunicationoverMANETs.QMRPpassesthepacketsbyusingmultiplelinkstothesamedestinationinordertoreducedelay.Thesameresultinmorereliabletransmissionaseventhoughonelinkfails,thenitwillnotaffectthroughputbadly.Inordertoachievebetterquality,QMRPisacross-layerapproachthattriestomakePhysicallayerandNetworklayerinteract.
Thefunctionalityofsomeschedulers(Sunetal.,2014)isbasedontheNetworkCodingmethodthatoptimizestheflowofdatainMANETbytransmitting“digitalevidence”aboutmessages.The“digitalevidence”is(itself)acompositeoftwoormoremessages.Whenthebitsof“digitalevidence”arriveatthedestination,thetransmittedmessageisdeducedratherthandirectlyreassembled.Originally,theNetworkCodingmethodwasproposedtobeusedattheNetworklayer.However,inwirelessnetworks,NetworkCodinghasbeenwidelyusedineitherMAClayerorPHYlayer(Firoozetal.,2013).Inbothcases,Networkcodingcanincrease the end-to-end throughput. Sun et al. (2014) proposed a Network Coding-basedPriority-packetSchedulerMultipathrouting(NC-PSM)inMANETusingfuzzycontrollers.The performance of NC-PSM was evaluated in terms of the PDR, packet overhead, andaverage end-to-end delay, when a packet is transmitted. NC-PSM is efficient, promisingandapplicableinMANETs.
Table 2. A comparison of opportunistic schedulers
Scheme Features Comments
OAR:(Sadeghietal.,2002)
Itsendsmultipleback-to-backdatapackets,wheneverthechannelqualityisgood.
Itensuresthatallnodesaregrantedchannelaccessforthesametime-shares(asachievedbysingle-rateIEEE802.11).
OSAR:(Wangetal.,2004a)
Ittakesadvantageofthemulti-userdiversityandadaptstherateaccordingly.
Itachievesmuchbetterperformancethanotherautorateschemes.
OSMA:(Wangetal.,2004b)
ItskeymechanismsaremulticastRTSandpriority-basedCTS.
OSMAexploitsthemultiuserdiversityintheCSMA/CA-basedwirelessnetworksandcanimprovethenetworkthroughput.
OSD:(Patil&Veciana,2007)
Ittriestoachieveopportunisticthroughputfordifferentusersandtraffic. Itdepictssimplecalladmissioncontrolscheme.
Zhengetal.(2007)
Itisadistributedopportunisticscheduling.Thedesiredtradeoffboilsdowntojudiciouslychoosingtheoptimalstoppingruleforchannelprobinganddistributedscheduling.
Theoptimalstrategiesarecharacterizedfromtwoperspectives:anetwork-centricperspectiveandauser-centricperspective.
COS:Chenetal.(2008)
ItmodifiestheIEEE802.11protocoltoimplementanoptimalschedulingpolicythatmaximizestheoverallnetworkperformancewhilesatisfyingtheQoSofindividualflows.
COSimplementationachieveshighernetworkthroughputandprovidesbetterQoSsupportthanpreviousworks.
Kimetal.(2013)
Basedonurgencymetricsandtheestimatedtransmissiondelayofeachpacket,itdeterminesthetransmissionorderanddroppolicytominimizethenodeurgency.
Itsupportsthedeliveryofdelay-sensitivedataoveramultihopMANETthatsupportsIEEE802.11multi-rateservice.
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CROSS-LAyER dESIGN SCHEdULING
Cross-layerdesignsolutionsuseotherlayerstoobtainbetterschedulesortheytrytoincludeintheinitialBSPproblemotherconstraints,suchasenergyconsumption.Suchsolutionsprovidejointroutingandscheduling,andpowerefficiency.InMANETs,thereistheinteractionbetweenroutingintheNetworklayerandaccesscontrolintheMAClayer.ThereisalsothecouplingbetweenpowercontrolinthePhysicallayerandschedulingintheMAClayer.Developersusecross-layerdesignsinordertoadaptthesystemtohighlyvariableMANETconditionsandtobettercontrolsystemperformanceproblems.Forexample,across-layeringdesigncanperformbothlocalandglobaladaptationstonetworkcongestion.TheMAC layer reacts locally tocongestionbyexponentialback-off.Whencongestion is high, this response is insufficient, requiring dual option compensation: either theforwardingmechanismcanreroutetraffictoavoidthebottleneckor,ifalternateroutesdonotexist,theoptimizationcanusetransportprotocolmechanismstofreezetraffictransmissions.
Manycross-layerroutingprotocolshavebeenproposedforMANETs(Alhosainyetal.,2014).TheCross-LayerSchedulingProtocol(CLSP)(Liuetal.,2006)incorporatesacross-layerschedulerattheMAClayerandconsidersmultipleconnectionswithdifferentQoSrequirements.InCLPS,eachconnectionemploysadaptivemodulationandcoding(AMC)schemeatthePhysicallayeroverwirelessfadingchannels.Eachconnectionisassignedapriority,whichisupdateddynamicallybasedonitschannelandservicestatus;theconnectionwiththehighestpriorityisscheduledeachtime.TheirschedulerprovidesdiverseQoSguarantees.Itusesthewirelessbandwidthefficiently,whileitenjoysflexibility,scalability,andlowimplementationcomplexity.
Wolfetal.(2006)proposedacross-layeranddistributedschedulingalgorithmforwirelessadhocnetworks.Intheiralgorithm(Lo-BaTS),thenodesfirstcoordinatetoacquireoneinitialtransmissionslotandthengainorloseslotsbasedonload.So,additionaltransmissionslotscanbereservedbythosenodesthatneedtoforwardmoretraffic.Thus,trafficbottleneckscanbealleviated.
WolfandRussell(2011)investigatedanewapproachforschedulingtransmissionsinaMANETbyemployingdirect-sequencespread-spectrum(DSSS);aspreadspectrummodulationtechniqueused to reduceoverall signal interference. InDSSSsystems,multiple-access interference (MAI)may be better tolerated, allowing higher levels of spatial reuse and a reduction in the overheadrequiredtoscheduletransmissions.TheauthorspresentedtheImmediateNeighborScheduling(INS)protocolthatcombinestheinterferencesuppressioncapabilityofDSSSmodulationwiththestableperformanceofatransmissionschedulingprotocol.TheINSisacross-layerprotocolthatleveragesthefeaturesofDSSStosupportgreaterend-to-endthroughputandterminalmobilityrates.INSisfullydistributedanddoesnot require two-waycommunication ina timeslot. Itdoesnot requireperiodicdowntimetomodifyorrecreatetheschedule.Instead,theschedulecontinuouslyadaptstothecurrentenvironment.ThesetoflinksusedinschedulingisdeterminedbyaggregateMAIpatternsinthenetworkandchannelgain.
TheModifiedProportionalFairnessmodelwithMulti-Hop(MPF-MH)queuescheduling(Sunetal.,2013)isacrosslayer-basedmodelthatcontrolstheQoSforend-usersinCognitiveRadio-basedMANETs.ACognitiveRadio(CR)isconfigureddynamicallytousethebestwirelesschannelsinitsvicinity.CRautomaticallydetectsavailablechannelsinwirelessspectrumandchangesitstransmissionorreceptionparameterstoallowmoreconcurrentwirelesscommunicationsinagivenspectrumbandatonelocation.TheCRfunctioncanprovidethereal-timechannelconditionsinaCR-basedMANETandcanhelpnodestoestablishnetworksduetoitsdynamicaccesscapability(Kim&Shin,2008).InMPF-MH,foreachtransmission,adaptivesub-channelcanbeselectedbyusingthereal-timechannelconditions.MPF-MHadaptivelyschedulestheradioresourcesforservingdifferenttypesofserviceinordertooptimizenetworkresourceswithoutdecreasingtheQoS.MPF-MHmodelensuresthatQoSisnotaffectedduringtransmission.Itcomputestheavailabilityofchannelsandbuffer.Then,itusesMACanalyzertocomputepacketpriorityandpacketschedulingbeforeselectingthetransmissionstrategy.ThedrawbackintheQoSscheduleroftheMPF-MHmodelisthatnoestimationiscarried
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outduringtransmission.Inthecaseofadditionofintermediatenodes,itrequiresregularupdatingofchannellistthatcausesincreasedoverheads.
Cross-Layer Schedulers for Power ControlEnergyefficiency is an important aspectof energy-aware routing inMANETs (Sarkar&Datta,2017).Theperiodicityofperfectlyperiodicschedulingcanbeusedtodecreaseenergyconsumption,andthustosavebatterylifeofMANETnodes(Kim&Glass,2015).Aperfectlyperiodicschedulerschedulesa“client”regularlyafterapredefinedamountoftime(theperiodoftheclient).TheadaptivealgorithmAdaptmin(Patil&Garg,2006)cancreateperfectlyperiodicschedulesanditsperformanceisclosetooptimalscheduling.LakshmiandRadha(2012)presentedaqueueschedulerscheme(called“SelfishSchedulerQueueMethodology”-SSQM)thatisawareofselfishnodes.SSQMprovidesareactivesolutiontoselfish(malicious)nodes.Itrequiresthecoordinationofthebuffermanagerandthequeuesthatformthepartofallparticipatingnodes.SSQMmanagesthenodesqueuesproperly;byforwardingpacketsfromthesourcenodetothedestinationthroughtheselfishnodes.Thecross-layerdesignframeworkproposedbyElBattandEphremides(2004)aims:1)tolimitmultiuserinterferencetoincreasesingle-hopthroughput;and2)toreducepowerconsumptiontoprolongbatterylife.Theirframeworkisfocusedonnextneighbourtransmissions,wherenodesarerequiredtosendinformationpacketstotheirrespectivereceiverssubjecttoaconstraintonthesignal-to-interference-and-noiseratio (SINR).Theproblemofmultipleaccesswassolvedvia twoalternatingphases: schedulingandpowercontrol.Thescheduleroftheirframeworkcoordinatesthetransmissionsofindependentuserstoeliminatestronglevelsofinterference(e.g.,self-interference)thatcannotbeovercomebypowercontrol.Powercontrolisexecutedinadistributedfashiontodeterminetheadmissiblepowervector,ifoneexists,thatcanbeusedbythescheduleduserstosatisfytheirsingle-hoptransmissionrequirements.Thisisdonefortwotypesofnetworks:TDMAandTDMA/code-division-multiple-accesswirelessadhocnetworks.TDMAMACprotocoltriestoallocatetimeslotstonodesinordertominimizepowerconsumptionandreducepacketdeliverydelayinnodes.
Wangetal.(2005)proposedajointdistributedinterference-basedTDMAlinkschedulingandpowercontrolalgorithmforadhocnetworkssupportingmulticasttraffic.Theiralgorithmeliminateslinks,whichcausemostinterference,inordertoallowtheremaininglinkstoreachanacceptableSINRlevel.SINRgivestheoreticalupperboundsonchannelcapacityinwirelessnetworks.
Tangetal.(2006)proposedajointlinkschedulingandpowercontrolTDMAalgorithmforamultihopwirelessnetworkwiththeobjectiveofmaximizingnetworkthroughput.Toachievethisgoal,theauthorsuseaMixedIntegerLinearProgramming(MILP)formulationtodescribetheproblemandthentheyeitherfindoptimalsolutionsorapplyapolynomial-timeheuristicalgorithm,theSerialLinearProgrammingRounding(SLPR)heuristic,tosolvetheproblem.ThebandwidthcanbefairlyallocatedamongalllinksbysolvingtheMILPformulationorbyusingtheheuristicalgorithmatthecostofaminorreductionofnetworkthroughput.However,itisdifficulttoevaluatetheperformanceoftheseheuristicalgorithms,whenoptimalsolutionsarenotknown.
BehzadandRubin(2007)developedamathematicalprogrammingformulationforminimizingtheframesizeinwirelessmultihopnetworks,basedonoptimaljointTDMAschedulingandpowercontrolunderthephysicalinterferencemodel.Itisbasedonapower-basedinterferencegraphthatdescribes the interference relationshipofevery two linksaccording to theSINRof the receiver.Then,basedonthisgraph,theauthorstriedtofindamaximallink-independentsetusingaheuristicalgorithm,theMinimumDegreeGreedyAlgorithm(MDGA).
LiandEphremides(2007)assumedaTDMA-basedwirelessadhocnetworkandprovidedacentralizedalgorithmofjointpowercontrol,scheduling,androuting.Theuseofthisjointalgorithmimprovesthenetworkperformanceintermsofthroughput,delay,andpowerconsumption.Thereisalsoatrade-offbetweenenergyconsumptionandnetworkthroughputordelayperformance.Maoetal.(2007)proposedajointlinkschedulingandpowercontrolalgorithmformany-to-onecommunicationsinwirelesssensornetworks.TheiralgorithmaimsatminimizingenergyconsumptionandTDMAframe
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length.Toobtainthisgoal,ahybridgeneticandparticleswarmoptimizationalgorithmisappliedtoenhancesearchingability.ThealgorithmoutperformstheclassicalnodeMaxDegreeFirstcoloringalgorithm,butitisnotsuitableforMANETshavinghighnodemobility.AsgharianandAmirshahi(2015)proposedanadaptiveanddistributedTDMAschedulingprotocolforMANET(AD-TDMA).AD-TDMAcausesenergysavingbyshowingagoodawake-sleepschedulingstateforMANETnodes.Ithasagoodperformanceagainstchangesinnetworktopology.TheAD-TDMAperformanceshowsasignificantimprovementinenergysavingandreductioninpacketdeliverydelay.
PadmavathyandJayashree(2017)presentedanenhanceddelaysensitivedatapacketschedulingalgorithm that is used to increase the energy efficiency, network lifetime, and throughput. Thisschedulerreducesthedelay,latency,anddroprate.Itschedulesthedatapacketsbasedonthehighweightedpriorityscheduling.Then,itforwardsthembasedonthechannelmedium,whetheritisbusyoridlestatetoavoidthedelayanddroprate.
Table3showsacomparisonofcross-layerschedulersforpowercontrol.
FUZZy-BASEd SCHEdULING
InMANETnodes, routingandschedulingdecisionsarebasedon incomplete input information,whilethedecisionprocessforfindingthepriorityindexofpacketsisfullofuncertainty.Afuzzyinferencesystemisflexibleandcapableofoperatingwithimprecisedata,andthusitishelpfultouseafuzzyinferencesysteminMANET.Theapplicationoffuzzylogicinordertofindthepriorityindex(output)ofthepacketscanimprovetheMANETperformance.Fuzzypriorityschedulerscancalculatethepriorityindexofthepacket,basedonvariousinputparameterslikeexpirytime,datarate,linkcongestion,packetsize,andqueuelength.Afuzzyinferencesystem(Figure4)consistsof
Table 3. A comparison of cross-layer schedulers for power control in MANETs
Scheme Features Comments
ElBattandEphremides(2004)
Transmissionsofindependentusersarecoordinatedtoeliminatestronglevelsofinterference.
Minimizesthepowerconsumption,butithasincreasedprocessingtime.
Wangetal.(2005) Eliminatesstronginterferersandenablestheentitledtransmitterstosolvethepowercontrolproblem.
Doesnotprovideaworst-caseanalysisonperformance.
Tangetal.(2006) Bandwidthcanbefairlyallocatedamongalllinks.Difficulttoevaluatetheperformanceoftheheuristicalgorithmswhenoptimalsolutionsarenotknown.
BehzadandRubin(2007) Minimizestheframelength Doesnotconsidertheaccumulationeffect
ofInterference.
Li&Ephremides(2007)
ΑcentralizedTDMAschedulingalgorithmofjointpowercontrol,scheduling,androuting.Achievesincreasedthroughput,decreaseddelayandimprovedpowerconsumption.
Duetoitstwo-stagenature,itneedsalargenumberofmessageexchangesbythenodes.
Maoetal.(2007)Ensuresapowerfulsearchingabilitytofindtheoptimalslotallocationscheme.Guaranteesthatthereisnoemptyslotduringscheduling.
Doesnotprovideanyperformanceguarantees.Doesnotconsiderlinkqualityduringscheduling.
AsgharianandAmirshahi(2015)
AdaptiveanddistributedTDMAschedulingprotocolwithagoodperformanceagainstnetworktopologychanges
Itcausesenergysavingbyshowingagoodawake-sleepschedulingstatefornodes.
PadmavathyandJayashree(2017) Anenhanceddelaysensitivepacketscheduler.
Itincreasesthethroughputof1.9Mbpsandenergyefficiencyandnetworklifetimeof85–90%.
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fourblocks:Fuzzifier,Defuzzifier,InferenceEngine,andFuzzyKnowledgeBase.Theprocessoffindingacrisppriorityindex,basedontheinputvaluesinvolvesthreesteps:fuzzification,inference,anddefuzzification.TheFuzzifierdecideshowtoconvertthecrispinputintoafuzzyinputtobeusedbytheInferenceengine.ThisisachievedbymappingthecrispinputtoasetofinputmembershipfunctionsstoredintheKnowledgebase.TheInferenceengineappliesreasoningtocomputethefuzzyoutputusingthe“IF-THEN”typefuzzyrules,whicharestoredintheKnowledgebase.Itisusedtoconvertthefuzzyinputstofuzzyoutputs.TheDefuzzifierconvertsthefuzzyoutputsintoacrispvalueusinganoutputmembershipfunctionstoredintheKnowledgebase.
TheFuzzy-BasedPriorityScheduler(FBPS)(Gomathy&Shanmugavel,2005)calculatesthepriorityofthepacketsanditsperformancewasstudiedwithinthecontextofmulticastroutingprotocols.FBPSwasevaluatedintermsofthequantitativemetricssuchasPDRandaverageend-to-enddelayandtheresultswereencouraging.TheFuzzyController-basedQoSRoutingAlgorithm(FQRA)(Sunetal.,2009)usesamulticlassschemeinMANETs.ItsperformancewasstudiedusingNS-2andevaluatedintermsofquantitativemeasuressuchaspathsuccessratio,averageend-to-enddelay,andthroughput.FQRAisefficient,promisingandapplicableinadhocnetworks.TheFuzzyLogicbasedPacketScheduling(FLPS)algorithm(Egajietal.,2013)requiresthreeinputs(datarate,queuesize,signal-to-noiseratio(SNR))incomparisontoearlierfuzzyalgorithms,whichrequiredtwoinputs.
BasedonMamdani-methodandSugeno-method fuzzy inference systems,Egaji et al. (2015)proposedtwoadaptiveprioritypacketschedulersforMANET.Theseschedulers(MamdaniandSugenoSchedulers)andtheirfuzzysystemsconsistofthreeinputvariables:datarate,SNRandqueuesize.Thefuzzydecisionsystemhasbeenoptimizedtoimproveitsefficiency.BothfuzzysystemswereverifiedusingtheMatlabfuzzytoolboxandtheperformanceofbothalgorithmswasevaluatedusingtheOPNETmodeler.Theresultswerecomparedtoanexistingfuzzyschedulerundervariousnetworkloadsforconstant-bit-rate(CBR)andvariable-bit-rate(VBR)traffic.Themeasuringmetricsforperformanceevaluationwere:end-to-enddelay,throughputandPDR.BothschedulersperformbetterthantheexistingschedulerforCBRtraffic.Theend-to-enddelayforMamdaniandSugenoschedulerwasreducedbyanaverageof52%and54%,respectively.ForCBRtraffic,theperformanceofthethroughputandPDRisverysimilartotheexistingschedulerbecauseofthecharacteristicofthetraffic.Thenetworkwasalsoatfullcapacity.MamdaniandSugenoschedulersalsoshowedabetterperformanceforVBRtraffic.Theend-to-enddelaywasreducedbyanaverageof38%and52%,respectively.BoththethroughputandPDRincreasedbyanaverageof53%and47%, respectively.TheMamdanischeduler ismorecomputationallycomplexthantheSugenoscheduler,eventhoughtheybothshowedsimilarnetworkperformance.Thus,theSugenoschedulerismoresuitableforreal-timeapplications.
Finally,Banerjeeetal.(2016)proposedaschedulingscheme(FSRP)thatprioritizesthereal-timedatapacketsbasedondeadlinetopacketsdelivery,relativevelocitybetweenconsecutiveroutersinthepathalongwiththeirresidualenergy.AReal-TimeFuzzycontroller(RTF)isusedinordertodefineastablepath.Forthisreason,theDeadlineImpact(LI),StabilityImpact(SI)andSourcePriority(SP)parametersareusedandformulatedbyafuzzyrule.Then,bycombining theseparameters,theygetRTF.RTFgivesranktoallpossiblepaths,andthenaccordingtothisrank,theproperpathisselectedforreal-timetraffic.
Table4showsacomparisonoffuzzy-basedschedulersforMANETs.
Figure 4. Basic fuzzy inference system
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CONCLUSION ANd FUTURE wORK
QoSschedulinginMANETscanbeachievedthroughmanytypesofscheduling.ThissurveypaperhaspresentedvariousdesignissuesofQoSschedulersinMANETs.Itmentionsalltherecentadvancesproposed inall typesof scheduling.Thesurveyalsoelaborates thevariousdesignchallengesofQoSschedulingand theirpossiblesolutions.Thecomparisonamongstvariousschedulersshowsthescenariosinwhichtheycanbeeffectivelyused,basedontheirrespectiveperformanceissues.
LatestschedulersforMANETsaremoreintelligentandefficientbyadoptingcross-layerdesignapproachesandmethodsthatoptimizetheflowofdata.Theyalsotrend:(1)toexploitintelligentnetworkcapabilitiessuchasthemultiplepacketreceptioncapabilityandthedynamicaccesscapabilityprovidedinCR-basedMANETs;and(2)touseintelligenceparadigms(e.g.,swarmintelligence).TheswarmintelligenceparadigmcanbeusedtosolvethedynamicoptimizationproblemofroutingandschedulinginMANETs.Forexample,SharmaandKumar(2014)proposedtheEnhancedSwarmIntelligence-BasedScheduler(ESIBS)whichusesswarmintelligencetocalculateanoptimumpathfrom source to destination. This implies that the collective behaviour of the decentralized, self-organizedMANETisusedforsuchcalculations.AnotherdirectionfordesigningefficientschedulersistouseintelligentprioritymethodsforarangeofprovidedservicesoverMANET.Forexample,Ahmadetal.(2016)proposedaDynamicPriorityBasedScheduling(DPBS)schemewhichusesaprioritysystemforvideostreamingoverMANET.PriorityisgivenintheorderofI(intracoded),P(predictivecoded)andB(bidirectionalpredictivecoded)frames.DPBShandlestheexpirytimeofthepacketsalongwiththedamagedacknowledgmentofpackets/frames.
Table 4. A comparison of fuzzy-based schedulers
Scheme Features Comments
FBPS:(Gomathy&Shanmugavel,2005) Itusesaprioritymechanism. Itcanbeusedincooperationofmulticastrouting
protocol.
FQRA:(Sunetal.2009) ItcalculatescrispQoSclass. ItattachesaQoSclasstoeachpacketinthenode
queue.
FLPS:(Egajietal.,2013)
Itrequiresthreeinputs(datarate,queuesize,SNR).
Thecrispvalueisgeneratedfromthefuzzifficationprocesswhichreflectsthepacketpriority.
MamdaniandSugenoschedulers:(Egajietal.,2015)
Adaptiveprioritypacketschedulers.Theirfuzzysystemsconsistof3inputvariables:datarate,signal-to-noiseratio,andqueuesize.
MamdanischedulerismorecomputationallycomplexthantheSugenoscheduler.Sugenoschedulerismoresuitableforreal-timeapplications.
NC-PSM:(Sunetal.,2014)
Itisamultipathroutingprotocolthatusesfuzzycontrollers.ItsschedulerisbasedonNetworkCoding.
NC-PSMisefficient,promisingandapplicableinMANETs.
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Dimitris Kanellopoulos is a member of the Educational Software Development Laboratory in the Department of Mathematics at the University of Patras, Greece. He received a Diploma in Electrical Engineering and a PhD in Electrical and Computer Engineering from the University of Patras. Since 1990, he was a research assistant in the Department of Electrical and Computer Engineering at the University of Patras and involved in several EU R&D projects. He is a member of the IEEE Technical Committee on Multimedia Communications. He serves as a reviewer for highly-respected journals such as: Journal of Network and Computer Applications (Elsevier), Int. Journal of Communication Systems (Wiley), J. of Systems and Software (Elsevier), Information Sciences (Elsevier), IETE Technical Review (Taylor & Francis) etc. He has served as a Technical Program Committee member to more than 70 int. conferences. His research interests include: multimedia networking, MANETs, WSNs, and intelligent information systems. He has many publications to his credit in int. journals and conferences at these areas. He has edited two books on “Multimedia networking” and serves as an editorial board member in some refereed journals.
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