Dynamic Multi-objective Cooperative Coevolutionary Scheduling for Mobile Underwater Wireless Sensor Networks

Abstract Mobile underwater wireless sensor networks (MUWSNs) play an important role in monitoring the marine environment.Many existing research works have engaged on the deployment optimization. Typical examples include rebuilding the network by moving sensors or healing coverage holes using mobile sensors. However, they didn’t make full use of dynamic characteristics of mobile sensors. This paper focuses on the scheduling problem of MUWSNs that consist of a small number of mobile sensors and a large number of fixed ones.To solve the problem, we take mobile sensors as cluster heads to formulate the problem as a multi-objective dynamic scheduling model of fixed sensors as mobile ones move. Then, a dynamic multi-objective cooperative coevolutionary optimization algorithm is developed through decomposing decision variables, designing a strategy to respond environmental changes, and a collaborative strategy for generating an approximate Pareto-optimal set. The feasibility of the proposed optimization model and the effectiveness of its solving algorithm is empirically demonstrated.