期刊名称：International Journal of Distributed Sensor Networks
印刷版ISSN：1550-1329
电子版ISSN：1550-1477
出版年度：2015
卷号：2015
DOI：10.1155/2015/619546
出版社：Hindawi Publishing Corporation
摘要：This paper studies the distributed energy efficient access point (AP) selection for cognitive sensors in the Internet of Things (IoT). The energy consumption is critical for the wireless sensor network (WSN), and central control would cause extremely high complexity due to the dense and dynamic deployment of sensors in the IoT. The desired approach is the one with lower computation complexity and much more flexibility, and the global optimization is also expected. We solve the multisensors AP selection problem by using the game theory and distributed learning algorithm. First, we formulate an energy oriented AP selection problem and propose a game model which is proved to be an exact potential game. Second, we design a distributed learning algorithm to obtain the globally optimal solution to the problem in a distributed manner. Finally, simulation results verify the theoretic analysis and show that the proposed approach could achieve much higher energy efficiency.
