A Swarm Optimization Based Power Aware Clustering Strategy for WSNs

Harendra S. Jangwan (1), Ashish Negi (2)
(1) GB Pant Engineering College, Ghurdauri, Pauri Garhwal, Postal Code- 246194 Uttrakhand, India
(2) GB Pant Engineering College, Ghurdauri, Pauri Garhwal, Postal Code- 246194 Uttrakhand, India
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How to cite (IJASEIT) :
Jangwan, Harendra S., and Ashish Negi. “A Swarm Optimization Based Power Aware Clustering Strategy for WSNs”. International Journal on Advanced Science, Engineering and Information Technology, vol. 7, no. 1, Feb. 2017, pp. 250-6, doi:10.18517/ijaseit.7.1.1638.
The technique of division of a wireless sensor network (WSN) into clusters has proved to most suitable for the reliable data communication inside the network. This approach also improves the throughput of the system along with other attributes such as rate of delivering data packet to the base station (BS) and overall energy dissipation of the sensor nodes in the network. This in turn results in the increased network lifetime. As the sensor nodes are operated by battery or some other source, this introduces a constraint in energy resource. Therefore, there is a strong need to develop a novel approach to overcome this constraint, since this phenomenon leads to the degradation of the network. The swarm intelligence approach is able to cope with all such pitfalls of WSNs. In this paper, we have presented a cluster-head (CH) selection technique which is based on swarm optimization with the main aim to increase the overall network lifetime. The proposed approach gives higher effects with regards to power utilization of nodes, data packets received at BS and stability period, and for this reason serves to be a higher performer as compared to Stable Election Protocol (SEP) and Enhance Threshold Sensitive Stable Election Protocol(ETSSEP). MATLAB simulation outcomes exhibit that the proposed clustering strategy outperforms the SEP and ETSSEP with regards to the above noted attributes.

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