Cluster-based Congestion Control for Supporting Multiple Classes of Traffic in Sensor Netwo

Cluster-basedCongestionControlforSupportingMultipleClassesofTraffic

inSensorNetworks

KyriakosKarenos,VanaKalogerakiandSrikanthV.Krishnamurthy

DepartmentofComputerScienceandEngineering

UniversityofCalifornia,Riverside

Email:{kkarenos,vana,krish}@cs.ucr.edu

Abstract

Inwirelesssensornetworks,multipleflowsfromdatacollectingsensorstoanaggregatingsinkcouldtraverse

pathsthatarelargelyinterferencecoupled.Theseinterfer-enceeffectsmanifestthemselvesascongestion,andcause

highpacketlossandarbitrarypacketdelays.Thisispar-

ticularlyproblematicinevent-basedsensornetworkswheresomeflowsareofgreaterimportancethanothersandre-

quirefidelityintermsofhigherpacketdeliveryandtimeli-

ness.InthispaperwepresentCOMUT(COngestioncontrolforMUlti-classTraffic),adistributedcluster-basedmecha-

nismforsupportingmultipleclassesoftrafficinsensornet-works.COMUTisbasedontheself-organizationofthenet-

workintoclusterseachofwhichautonomouslyandproac-

tivelymonitorscongestionwithinitslocalizedscope.Theclustersthenexchangeappropriateinformationtofacilitate

systemwideratecontrol.Oursimulationresultsdemon-

stratethatourtechniquesarehighlyeffectiveindealingwithmultiple,randomlyinitiatedflows.

1.Introduction

Inthispaperwepresentascalableanddistributedframe-

workforeliminatingcongestionandsupportingmultipleclassesofflowsinevent-basedsensornetworks.Incontrast

tomonitoringapplications,whereinsensorsaredeployed

toreportperiodicdata,inevent-basedsensornetworks,re-portsareproducedonlyupontheobservationofspecific

eventsthatsatisfycertainpre-specifiedconditions;atypi-

calexamplemightbetheincreaseintheobservedtempera-turebeyondapresetthreshold.

Weconsidersensornetworksthatconsistofarelativelylargenumberofcheap,disposablesensorswhichreportto

onlyasmallnumberofaggregatingsinks.Collisionsof

packetsfromsimultaneous,interference-coupledflowscre-atecongestedhotspotswhich,inturn,causeflowstoex-

periencedelaysandpacketdrops.Theproblembecomesmorecriticalinapplicationssuchasdisasterrecoverymis-

sions,wherepacketsfromsomeflowsarelikelytobeofgreaterimportancethanothers.Maintainingahighdelivery

ratioforthemoreimportantflowsiscriticalinthesenet-

works.Ourworktargetsthesescenariosandhastwospe-cificbutinter-relatedconstituentobjectives:(i)provision

ofdistributedmechanismsforcongestioncontroland,(ii)

managementofflowsfrommultipleclasses,i.e.,ofhigherversuslowerimportance.

Traditionalcongestioncontrolapproachesutilizeend-to-

endorhop-by-hop(orcombinatory)techniques[4,15]butconsideronlyasingleclassofpackets.End-to-endtech-

niques[13]requirethesinktoregulatethesensors’sending

rate.However,becausetrafficvolumeishigherintheprox-imityofthesink,theregulatoryupdatessentbythesink

maybethrottledatthesource.Ontheotherhand,hop-by-

hop,backpressuretechniques[15]arereactiveinnatureandmightnotcreateresponsivenessinatimelyfashion.

Previouslyproposedservicedifferentiationtechniques

havenotconsideredcongestionoritseffects[11,18].Ad-missioncontroltechniquesproposedforwireless,adhoc

networks[11,19],considerthenetworkloadandthusreg-

ulatecongestionindirectly.However,thesemethodsarelikelytobecomputationandoverheadintensiveinthepres-

enceofmultipleclassesofflowsandwill,hence,beunsuit-

ableforsensornetworks.

InthispaperwepresentCOMUT(COngestioncontrol

forMUlti-classTraffic),aframeworkthatprovidesscalable

anddistributedcluster-basedmechanismsforsupportingmultipleclassesoftrafficinsensornetworks.Inthetech-

niquespreviouslydiscussed,congestionisestimatedand

actionistakenonaper-nodebasis.Thedistinguishingchar-acteristicofourapproachisthatCOMUTisbasedonthe

self-organizationofthenetworkintoclusterseachofwhichautonomouslyandproactivelymonitorscongestionwithin

itslocalizedscope.Toaccomplishthis,sentinelrolesare

assignedtosensorstoproactivelymonitornetworkstatis-ticsandinferthecollectivelevelofcongestion.Regulation

ofsensorrates(per-cluster)andcoordinationbetweenclus-

0-7803-9246-9/05/$20.00 © 2005 IEEE1EmNetS-IIternodesisachievedbyexchangingonlysmallvolumesof

controlinformationbetweenthesentinelsensorsalongflowpaths.Sensorclusteringisbeneficialinthatagroupofsen-

sorscancapturethebehavioralinteractionsbetweenflows.

Thesensorsinaclusteradjusttheirratesaspertherela-tivelevelofimportanceoftheeventstobereportedandthe

congestionstateenroutethesink,thusimprovingthetime-linessofdatadeliveryforhighimportanceflowsandtheef-

ficiencywithwhichtheavailablebandwidthissharedbe-

tweentheflows.Thisprocessimprovesthetimelinessofdatadeliveryseenbyflowsofhighimportancewhileim-

provingtheefficiencywithwhichtheavailablebandwidth

issharedbetweenflows.

Wesummarizeourcontributionsbelow:Wepro-

poseaframeworkforcongestionandratecontrolinhighlydynamicandunpredictableeventbasedsensorsys-

temswhereinmultipleclassesofflowsaretobesupported.Ourframeworkconsistsofthefollowingcomponents:(i)A

distributedandscalablemechanismthatfacilitatestheclus-

teringofsensorsandallowsfortheadjustmentofthesendingratepercluster.(ii)Adecentralizedmethodol-

ogyforintra-andinter-cluster,per-pathestimationof