Cluster Formation based Comparison of Genetic Algorithm and Particle swarm Optimization Algorithm in Wireless Sensor Network
Keywords:
Genetic Algorithm Clustering, Energy efficiency, Particle Swarm OptimizationAbstract
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).
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