Bio-Inspired Computation for Solving the Optimal Coverage Problem in Wireless Sensor Networks: A Binary Particle Swarm Optimization Approach

摘要: The optimal coverage problem (OCP) in a wireless sensor network is to activate as few nodes possible monitor the area order save energy, while at same time meeting full surveillance requirement. This chapter formulates OCP 0/1 programming and proposes use binary particle swarm optimization (BPSO) algorithm solve problem. First, modeled problem, where 1 means node active 0 turned off. model provides very natural intuitive way interpret representation real network. Second, by considering that bio-inspired computation algorithms have strong global ability are suitable for solving this BPSO approach OCP, resulting an efficient solution OCP. Simulations been conducted evaluate performance of proposed approach. Moreover, genetic (GA) adopted comparison experiments demonstrate advantages experimental results show our not only outperforms state-of-the-art approaches minimizing active-node number, but also performs better than GA under different scales densities. has good maximizing disjoint-set number when compared with traditional heuristic approaches.