A New Clustering Algorithm Using Adaptive Discrete Particle Swarm Optimization in Wireless Sensor Ne

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Wireless sensor networks ( WSNs ) are mainly characterized by their limited and non-replenishable energy supply.Hence,the energy efficiency of the infrastructure greatly affects the network lifetime.Clustering is one of the methods that can expand the lifespan of the whole network by grouping the sensor nodes according to some criteria and choosing the appropriate cluster heads (CHs).The balanced load of the CHs has an important effect on the energy consumption balancing and lifespan of the whole network.Therefore,a new CHs election method is proposed using an adaptive discrete particle swarm optimization ( ADPSO ) algorithm with a fitness value function considering the load balancing and energy consumption.Simulation results not only demonstrate that the proposed algorithm can have better performance in load balancing than low-energy adaptive clustering hierarchy (LEACH),hybrid energy-efficient distributed clustering (HEED),and dynamic clustering algorithm with balanced load (DCBL),but also imply that the proposed algorithm can extend the network lifetime more.
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