Multi Parameters Based Heterogeneous Clustering Algorithm for Energy Optimization in WSN

Abstract

Wireless Sensor Network (WSN) consists of tiny sensor nodes that are able to sense data from vicinity and send this data to the sink or Base Station (BS). The main issue during data collection is the non-rechargeable energy resource or battery. So the data collection should be energy efficient for long use of WSN. As we know that clustering is one of the most efficient technique for saving energy in WSN. Purpose of the paper is to find out multi-factor based clustering process having four conflicting factors: a) delay based on remaining energy, maximum power transmission etc., b) average lifetime of normal sensor nodes, c) lifetime of CHs, and d) maximum power consumption by any normal node. The algorithm is developed with an economical approach for finding CHs using a fitness function. Optimal path is also found utilizing the ${\prime}d_0^{\prime}$ distance. Results are far better than the traditional algorithms.