ABSTRACT
In clustered WSNs, the Cluster Head (CH) is viewed as a gateway, and various operations are carried out by gateways, such as data collection, aggregation, and transmission. Inadequate clustering may decrease the lifetime of the network. Therefore, designing an efficient clustering technique is an essential objective in WSNs. To obtain the objective, this chapter proposes a clustering technique based on the Shued Complex Evolution of Particle Swarm Optimization (SCE-PSO) with a novel fitness function. Experimental results are compared with the existing load balancing methods, such as NGA, SBLB, SGA, and NLDLB. Experimental results and analysis show that the proposed SCE-PSO clustering algorithm improves the lifetime of the network s relative to other approaches as mentioned above.
