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Comparison between Genetic Algorithm and PSO for Wireless Sensor Networks
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DOI：10.1007/978-981-10-5544-7_39.png)
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Abstract
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One of the most promising algorithms for network optimization is the particle swarm optimization (PSO) and genetic algorithm (GA). The paper is about comparing these two as applied to wireless sensor networks. If a sink is placed at a longer distance from the sensors then the battery life (energy) drains faster, and it reduces the life of the network. Our analysis shows that optimized clustering technique of sensors can minimize the communication distance and can help to increase the network stability. GA and PSO can optimize the cluster formation of sensors. Simulation results have shown us that PSO performs better than GA for clustering algorithms in wireless sensor networks.
Keywords:
Wireless sensors
Network
Ad hoc networks
Clustering
Genetic algorithm
Particle swarm optimization
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