Energy Efficient Clustering Algorithm for Surveillance and Reconnaissance Applications in Wireless Sensor Networks 


Vol. 37,  No. 11, pp. 1172-1183, Nov.  2012


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  Abstract

Wireless Sensor Networks(WSNs) are used in diverse applications. In general, sensor nodes that are easily deployed on specific areas have many resource constrains such as battery power, memory sizes, MCUs, RFs and so on. Hence, first of all, the efficient energy consumption is strongly required in WSNs. In terms of event states, event-driven deliverly model (i.e. surveillance and reconnaissance applications) has several characteristics. On the basis of such a model, clustering algorithms can be mostly used to manage sensor nodes’ energy efficiently owing to the advantages of data aggregations. Since a specific node collects packets from its child nodes in a network topology and aggregates them into one packet to relay them once, amount of transmitted packets to a sink node can be reduced. However, most clustering algorithms have been designed without considering can be reduced. However, most clustering algorithms have been designed without considering characteristics of event-driven deliverly model, which results in some problems. In this paper, we propose enhanced clustering algorithms regarding with both targets’ movement and energy efficiency in order for applications of surveillance and reconnaissance. These algorithms form some clusters to contend locally between nodes, which have already detected certain targets, by using a method which called CHEW (Cluster Head Election Window). Therefore, our proposed algorithms enable to reduce not only the cost of cluster maintenance, but also energy consumption. In conclusion, we analyze traces of the clusters’ movements according to targets’ locations, evaluate the traces’ results and we compare our algorithms with others through simulations. Finally, we verify our algorithms use power energy efficiently.

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  Cite this article

[IEEE Style]

J. Kong, J. Lee, J. Kang, D. Eom, "Energy Efficient Clustering Algorithm for Surveillance and Reconnaissance Applications in Wireless Sensor Networks," The Journal of Korean Institute of Communications and Information Sciences, vol. 37, no. 11, pp. 1172-1183, 2012. DOI: .

[ACM Style]

Joon-Ik Kong, Jae-Ho Lee, Jiheon Kang, and Doo-Seop Eom. 2012. Energy Efficient Clustering Algorithm for Surveillance and Reconnaissance Applications in Wireless Sensor Networks. The Journal of Korean Institute of Communications and Information Sciences, 37, 11, (2012), 1172-1183. DOI: .

[KICS Style]

Joon-Ik Kong, Jae-Ho Lee, Jiheon Kang, Doo-Seop Eom, "Energy Efficient Clustering Algorithm for Surveillance and Reconnaissance Applications in Wireless Sensor Networks," The Journal of Korean Institute of Communications and Information Sciences, vol. 37, no. 11, pp. 1172-1183, 11. 2012.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880