Cluster Formation based Comparison of Genetic Algorithm and Particle swarm Optimization Algorithm in Wireless Sensor Network

A. Garg¹ , N. Batra² , I. Taneja³ , A. Bhatnagar⁴ , A. Yadav⁵ , S. Kumar⁶

Section:Research Paper, Product Type: Isroset-Journal
Vol.5 , Issue.2 , pp.14-20, Apr-2017

Online published on Apr 30, 2017

Copyright © A. Garg, N. Batra, I. Taneja, A. Bhatnagar, A. Yadav, S. Kumar . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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Abstract :
Wireless Sensor Network is a network of small sensor nodes which sense the environment for various monitoring purposes of real life applications like military or commercial, which are required to be deployed in areas with no connectivity to the outside world. But, these nodes come with a limitation of having short battery life which needs to be recovered by applying various optimization techniques. In this paper, we are comparing two optimization algorithms that are Genetic algorithm and Particle Swarm Optimization algorithm, on the basis of their cluster head selection and cluster formation techniques to solve the problem of energy consumption by sensor nodes. We are experimenting with the different number of clusters to check the efficiency of each algorithm in MATLAB (simulation tool).

Key-Words / Index Term :
Genetic Algorithm Clustering, Energy efficiency, Particle Swarm Optimization, Wireless Sensor Networks

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