Abstract

Energy efficiency and sensing accuracy have both been attractive research fields in sensor networks. Achieving both objectives is possible in a compromise model. In this paper we formulate one such problem and use a game theoretic approach for its solution. The interaction between sensor nodes is modeled as a cooperative bargaining game, where individual sensors cooperate for achieving the application sensing requirements while minimizing and balancing the energy consumption. We use Kalai-Smordinsky Bargaining Solution to find a distribution rule that optimizes the trade-off in the compromise problem. Based on the distribution rule, we propose a lightweight distributed algorithm in order to schedule nodes for performing the sensing task. Simulation shows a superiority in terms of scalability over a similar earlier work, while a comparable achievement in network lifetime improvement is obtained at the same time.

@inproceedings{Networked Sensing Systems (INSS), 2010 Seventh International Conference on,
isbn = {978-1-4244-7910-8},
pages = {73-76},
publisher = {IEEE CONFERENCE PUBLICATIONS},
}