ENERGY EFFICIENT WIRELESS CLUSTERING USING BIOGEOGRAPHY BASED OPTIMIZATION.

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Anu Kadian

Abstract

Wireless sensor networks are constrained with limited battery lifetime. WSN consist of sensor nodes and cluster heads which are battery operated. hence efficient usage of cluster head energy becomes a crucial factor in the long run operation of a WSN. Many artificial algorithms have been implemented in the past to achieve energy efficient wireless clustering. we propose a new artificial intelligence based wireless clustering algorithm that performs better than all the existing algorithms. We use Biogeography Based Optimization to minimize the energy consumption by cluster heads in a WSN. The proposed algorithm outperforms all the existing algorithms.

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