A Performance Evaluation of a Coverage Compensation based Algorithm for Wireless Sensor Networks

Recent years, coverage has been widely investigated as one of the fundamental quality measurements of wireless sensor networks. In order to maintaining the coverage while saving energy of networks, algorithms have been developed to keep a minimum cover set of sensors working and turn off the redundant; sensors. Generally, centralized algorithms can give a better result than distributed algorithms in terms of the number of active sensors. However, the heavy computation requirements and message overhead for collecting geographical location data keep centralized algorithms out of most distributed scenarios. In this article, Based on the idea of coverage compensation a distributed node partition algorithm for random deployments is presented to generate a minimum cover set by using the optimal node distributions created by the centralized algorithms such as GA. A Genetic Algorithm for coverage is proposed too to demonstrate how an optimal coverage node distribution created by CA can be used in a distributed scenario. Ours works are simulated on JGAP and NS2. The simulation result shows that our partition algorithm based on coverage compensation can achieve the same performance as OCOPS in terms of coverage and number of active sensors while using less control messages.