An Extensible Particles Swarm Optimization for Energy-Effective Cluster Management of Underwater Sensor Networks

Acoustic communication networks in underwater environment are the key technology to explore global ocean. There are major challenges including (1) lack of stable and sufficient power supply, (2) disable of radio frequency signal and (3) no communication protocol designed for underwater environment. Thus, acoustic so far is the only media suitable to operate for underwater communication. In this paper, we study the technology of underwater acoustic communication to support underwater sensor networks. Toward the energy-effective goal, a cluster-based sensor network is assumed. The energy-dissipation of sensor nodes is optimized by biological computing such as Particle Swarm Optimization (PSO). The objective function of sensor node clustering is formulized to constraint on the network coverage and energy dissipation. The problem of dual-objective optimization is solved by the proposed extensible PSO (ePSO). ePSOis an innovation from traditional PSO. The major innovation is to offer an extensible particle structure and to enable more flexible search for optimal solutions in space. The experimental results demonstrate that the proposed ePSO effectively and fast tackles multi-objective optimization problem. The application of ePSO on underwater acoustic communication systems shows the feasibility in real world.