A hybrid bacteria foraging using Particle Swarm Optimization algorithm for clustering in wireless sensor networks

Prolonged network lifetime and lowerenergy consumption are important requirements for wireless sensor network applications. Information processing and communication capabilities of the sensor nodes consumes more energy and directly affect the life time of the network. Clustering is commonly used for improving the lifetime of the network and to reduce the energy consumption. we propose a hybrid approach involving Bacteria Foraging Algorithm (BFA) and Particle Swarm Optimization (PSO) applied to traditional clustering based protocol like LEACH-C that forms the k-optimal clusters by identifying the suitable cluster head. This algorithm searches the random direction in the tumble behavior of each bacteria for using the local best and global best position obtained by PSO. The performance of the proposed hybrid algorithm is compared with the BFA algorithm and LEACH-C. Simulation studies using NS2showed the improvement in network lifetime and reduced energy consumption.