Energy efficient clustering method for wireless sensor network

Abstract

Wireless sensor has attained wide interest across various industries due to availability of low cost sensor devices. Preserving battery/energy of these sensor devices are most desired. Recently, many approaches has been presented to improve lifetime of sensor networks adopting clustering technique. Cluster head selection play an important factor in improving lifetime of cluster based network. For improving cluster head selection multi-objective function are presented in recent time by adopting evolutionary computing and metaheuristic algorithm. However, the existing model incurs computation overhead due to NP-Hard problem and connectivity issues is not considered. Thus affecting network performance. To address the research issues, this work present a novel Multi-objective imperialist competitive algorithm (MOICA) for cluster head selection and routing optimization. Experiment are conducted to evaluate the performance of MOICA over LEACH in term of lifetime performance considering first sensor node death and 75% sensor node death. The outcome shows an average lifetime performance improvement of 56.32% in case of first sensor node death and 53.61% in case of 75% sensor node death.Therefore, MOICA achieves significance improvement over LEACH based protocols.