Hybrid Coverage Vulnerability Recovery in WSNs Based on Q Learning Game Theory
Aiming at distributed wireless sensor networks in harsh environment,in order to reduce cost and recovery ability,a hy-brid coverage vulnerability recovery method of wireless sensor networks based on Q-Learning game theory was proposed.Firstly,a hybrid algorithm which could narrow the coverage gap in a decentralized,dynamic and autonomous way was designed.The concept of game theory based on Q-learning algorithm and integrates two coverage control schemes:node relocation and power transmission adjustment were used.For the developed potential game theory,sensor nodes could only use local familiarity to re-cover coverage vulnerabilities,so as to reduce the coverage gap.Each sensor node selects nodes to place and adjust the sensing range.Finally,the simulation results show that the proposed method can maintain the overall coverage of the network under the condition of continuous random coverage vulnerabilities.
万方数据
维普
