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Multi-Objective Spider Monkey Optimization for Energy Efficient Clustering and Routing in Wireless Sensor Networks
R. Avudaiammal, S. Duraimurugan, V. Sivasankaran and P. Jayarajan
In wireless sensor networks (WSN), the gateways far away from the base station (BS) use the gateways nearer to the BS to forward the data. It causes heavy traffic to the gateways in proximity with the BS which in turn causes additional energy consumption and reduction in network lifetime. In order to overcome these issues, multi objective based spider monkey optimization (MOSMO) has been presented to balance the load and to improve the network lifetime through energy efficient routing and clustering. The objective functions such as routing fitness and clustering fitness have been considered for optimal routing and clustering. The performance of the proposed scheme is compared with the Particle Swarm Optimization (PSO) and Grey Wolf Optimization (GWO) based scheme in terms of delay, energy consumption, delivery ratio, throughput and network lifetime with various node densities. The results show that the reduction in delay and energy consumption is about 18% and 17% respectively whereas improvement in delivery ratio, throughput and network lifetime is about 15%, 24% and 19% respectively when compared to the existing PSO and GWO methods.
Keywords: Wireless sensor network (WSN), load balancing, clustering, routing and spider monkey optimization (SMO), MOSMO