PROJECT TITLE :

Game-Theoretic Multi-Channel Multi-Access in Energy Harvesting Wireless Sensor Networks

ABSTRACT:

Energy harvesting (EH) has been proposed as a promising technology to extend the lifetime of wireless sensor networks (WSNs) by continuously harvesting inexperienced/renewable energy. But, the intermittent and random EH process as well because the complexity in achieving world network info decision for economical energy management and distributed resource optimization. Considering the complex interactions among individual sensors, we tend to use the game theory to perform distributed optimization for the general multi-channel multi-access drawback in an EH-WSN, where strict delay constraints are imposed for the information transmission. Sensors’ competition for channel access is formulated as a non-cooperative game, that is proved to be an ordinal potential game that has at least one Nash equilibrium (NE). Furthermore, all the NE of the sport is proved to be Pareto optimal, and Jain’s fairness index certain of the NE is theoretically derived. Finally, we have a tendency to style a fully distributed, on-line learning algorithm for the multi-channel multi-access within the EH-WSN, that is proved to converge to the NE of the formulated game. Simulation results validate the effectiveness of the proposed algorithm.