Cluster Head Selection in Mobile Ad-hoc Network (MANET) Using ART1 Neural Network

Abstract

Mobile ad-hoc network or simply MANET is one of the better choices for communication in various fields like military, environment, tracking etc. due to its cost effectiveness. Limited battery power is a major challenge in MANET for many applications. Hence, to handle this problem, we more often work on routing technique like DSR, AODV, DSDV, OLTP. Therefore it consumes less power during data transfer from mobile nodes to the respective base stations. In today’s research artificial neural network has become one of the most promising real time problems solving technique which is being used widely in many real time applications. It is also best suited for the cluster head selection in MANET. In this paper, ART1, an unsupervised learning technique of artificial neural network has been implemented to select the cluster head in routing. Simulation result shows that 58% network lifetime enhancement is achieved. KeywordsMANET, cluster head, ART1 neural network, unsupervised learning. African Journal of Computing & ICT Reference Format: S. Gangwar, K. Kumar & M. Mittal (2015) Cluster Head Selection in Mobile Ad-hoc Network (MANET) Using ART1 Neural Network. Afr J. of Comp & ICTs. Vol 8, No. 1. Pp 197-204.

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Cite this paper

@inproceedings{Gangwar2015ClusterHS, title={Cluster Head Selection in Mobile Ad-hoc Network (MANET) Using ART1 Neural Network}, author={Shalini Gangwar}, year={2015} }