Recent Progress on QoS Scheduling for Mobile Ad Hoc …...for Mobile Ad Hoc Networks Dimitris N....

DOI: 10.4018/JOEUC.2019070103

Journal of Organizational and End User ComputingVolume 31 • Issue 3 • July-September 2019

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

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

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

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;

• 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)]

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

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

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.

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

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.

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.

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.

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.

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)

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

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.

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

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

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

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.

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

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

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

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%.

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

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

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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