Quasi-physical and quasi-sociological method for optimizing the area covering of wireless sensor network

An optimizing model is presented for the area covering problem of Wireless Sensor Network (WSN), which is a NP-hard problem having exponential complicated degree. Three quasi-physical and quasi-sociological methods are designed for the problem, and they are quasi-gravitation method, quasi-coulomb force method, and common enrichment method. Based on these methods, a quasi-physical and quasi-sociological algorithm (QPQSA) is proposed, which is a distributed iterative algorithm utilizing the sensor nodes' local information. The simulation results demonstrate that, for a target area with complex boundary, WSN can achieve an optimized coverage from a random initial coverage by self-organized moving and power controlling. After optimizing, the network life-span has been lengthened 35.84%, and the coverage rate has been improved from 72.93% to 98.77%.