An Energy Efficient Clustering Algorithmic Approach Based on Hidden Markov Model in Wireless Sensor Networks

Abstract

Wireless Sensor Networks (WSN) are widely used in various diverse applications from health care to Structural monitoring and disaster management etc. Some of these applications are time bound and critical, few of them require basic monitoring operations. The sensor nodes have limited battery; apart from this link failures and node death are unpredictable in WSN environment. The energy consumption is maximal in communications, than in sensing and computational task. The communication between sensor node and sink largely depends on clustering algorithm and routing protocols used by the network. An effective clustering method will improve the energy efficiency and lifetime of the network. WSN have dynamic topology hence it is important to have dynamic clustering and routing techniques. In dynamic clustering new CH and cluster are formed in each round, this causes a lot of control and acknowledgement messages to be exchanged in each round. In small and medium size network, it is important to limit communication and computations at the node level. newline