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1、UsingClusteringInformationforSensorNetworkLocalization1HaowenChanMarkLukAdrianPerrig1ThisresearchwassupportedinpartbyCyLabatCarnegieMellonundergrantDAAD19-02-1-0389fromtheArmyResearchOffice,andgrantCAREERCNS-0347807fromNSF,andbyagiftfromBosch.Theviewsandconclusionscontainedinthispaperar
2、ethoseoftheauthorsandshouldnotbeinterpretedasrepresentingtheofficialpolicies,eitherexpressedorimplied,ofBosch,CarnegieMellonUniversity,NSF,theArmyResearchOffice,theU.S.Governmentoranyofitsagencies.SensornetworklocalizationcontinuesAbstracttobeanimportantresearchchallenge.Thegoaloflocaliz
3、ationistoassigngeographiccoordinatestoeachnodeinthesensornetwork.Localizationschemesforsensornetworksystemsshouldworkwithinexpensiveoff-the-shelfhardware,scaletolargenetworks,andalsoachievegoodaccuracyinthepresenceofirregularitiesandobstaclesinthedeploymentarea.Wepresentanovelapproachf
4、orlocalizationthatcansatisfyallofthesedesiredproperties.Recentdevelopmentsinsensornetworkclusteringalgorithmshaveresultedindistributedalgorithmsthatproducehighlyregularclusters.Weproposetomakeuseofthisregularitytoinformourlocalizationalgorithm.Themainadvantagesofourapproacharethatourpr
5、otocolrequiresonlythreerandomly-placednodesthatknowtheirgeographiccoordinates,anddoesnotrequireanyrangingorpositioningequip-ment(i.e.,nosignalstrengthmeasurement,ultrasoundranging,ordirectionalantennasareneeded).Sofar,onlytheDV-Hoplocalizationmechanismworkedwiththesameassumptions[1].We
6、showthatourproposedapproachmayoutperformDV-Hopincertainscenarios,inparticularwhenthereexistlargeobstaclesinthedeployment®eld,orwhenthedeploymentareaisfreeofobstaclesbutthenumberofanchorsislimited.0.1IntroductionManywirelesssensornetworkapplicationsrequireinformationaboutthegeographiclo
7、cationofeachsensornode.Besidesthetypicalapplicationofcorrelatingsensorreadingswithphysicallocations,approximategeographicallocalizationisalsoneededforapplicationssuchaslocation-aidedrouting[2],geographicrouting[3],geographicroutingwithimprecisegeographiccoordinates[4,5],geographichas
