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Fuzzy-Controlled Energy-Efficient Weight-Based Two Hop Clustering for Multicast Communication in Mobile Ad Hoc Networks

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Swarm, Evolutionary, and Memetic Computing (SEMCCO 2011)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7076))

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Abstract

A mobile ad hoc network is an infrastructure-less network where the nodes are free to move independently in any direction. The technique of clustering is used to divide a large network into several sub-networks. Inherent dynamism of nodes gives rise to unpredictable topological structure in ad hoc networks which complicates the clustering process. Moreover, since mobile nodes are battery powered, energy saving is required to increase node lifetime and maintain network connectivity. In this paper we propose a fuzzy-controlled energy-efficient weight-based clustering algorithm (FEW-CA) for mobile ad hoc networks. A fuzzy controller named Cluster-head Elector (CE) is embedded in each node n i which computes weight of node n i . If n i is not already member of any cluster and its weight is greater than a pre-defined threshold, then it is elected as a cluster-head and a cluster is formed with 1-hop and 2-hop neighbors of n i who are not already members of any other cluster. FEW-CA does not allow any node to become member of more then one cluster simultaneously. Simulation results firmly establish that our algorithm performs better than existing state-of-the-art broadcast algorithms.

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© 2011 Springer-Verlag Berlin Heidelberg

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Banerjee, A., Dutta, P., Ghosh, S. (2011). Fuzzy-Controlled Energy-Efficient Weight-Based Two Hop Clustering for Multicast Communication in Mobile Ad Hoc Networks. In: Panigrahi, B.K., Suganthan, P.N., Das, S., Satapathy, S.C. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2011. Lecture Notes in Computer Science, vol 7076. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27172-4_62

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  • DOI: https://doi.org/10.1007/978-3-642-27172-4_62

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-27171-7

  • Online ISBN: 978-3-642-27172-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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