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چكيده انگليسي :

86 A Semi Localized Algorithm for Cluster Head Selection for Target Tracking in Grid Wireless Sensor Network Masoud Zarifneshat m zarifneshat@ec iut ac ir Sunday May 22nd 2011 Departement of Electrical and Computer Engineering Isfahan University of Technology Isfahan 84156 83111 Iran Degree M Sc Language Persian Dr Pejman Khadivi Assistant Prof pkhadivi@ec iut ac irAbstractWireless sensor networkingis a research area which is growing very fast and has attracted too much attentionin the past few years This has been caused by advances in the development of low cost sensor devicesequipped with wireless network interfaces Since a large number of sensor nodes are required to be linkedtogether in these networks there will be new challenges alongside with new applications coming up for suchnetworks There are a lot of applications in many fields defined for wireless sensor networks includingmedical industrial and home networks One of the most important applications of wireless sensor networksis target tracking In this application the sensor nodes in the network are used to sense and detect a target andtrack it until it goes out of the monitored field These nodes are wireless and usually run on batteries and thisis the most important power source they have In some cases wireless nodes are deployed in harsh placeswith minimum accessibility so minimizing the power consumption is a very important issue which hasattracted a lot of attention through years Hence in this research we tried to reduce power consumption inwireless sensor networks with the application of target tracking by introducing two new algorithms At firstwe introduced different mobility models which are used in simulation of wireless ad hoc networks to inspectthe performance of the proposed algorithms These models were inspected according to the average speed ofmobile node and its direction The goal of this analysis is inspection of the relation between the averagespeed of mobile node and its tendency to change its direction in various mobility models We concluded thatthe time a mobile node would spend on a constant direction cannot be predicted according to its speed Othermovement parameters of mobility models were also studied Average traveled distance in constant directionin different speeds was calculated The other calculated parameter was the pattern of locations where themobile node changed its direction The proposed algorithm is a cluster based target tracking algorithm whichis based on dynamic clustering It is a semi localized cluster head selection algorithm which consumes muchless power compared to its distributed version First a basic clustering algorithm was introduced and then wemodified this algorithm to create our proposed algorithm In basic algorithm there is a distributed processwhich selects cluster head and cluster members cooperatively In the proposed algorithm cluster head andcluster members of next cluster are chosen by current cluster head The simulations show a noticeablereduction in power consumption in terms of reduction in sent and received messages and reduction in samplerate of sensing subsystem Proposed algorithm works well with low speed targets but it loses its powersavings as the number of target misses increase Hence another algorithm is proposed that can reduce targetmisses by recording the correct place a target goes in the respective area after target is lost and recovered Inthis algorithm each time the target is lost a recovery process starts and finds the target This algorithmrecords some sort of target movement history Simulations show meaningful reduction in the number oftarget misses for targets which move according to freeway mobility model KeywordsTarget Tracking Mobility Models Dynamic Clustering Target Movement History

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