Game Theoretic Reward Based Adaptive Data Communication in Wireless Sensor Networks

Selfish or non-cooperative behavior of nodes can degrade the performance of a wireless sensor network in many ways. These nodes can cause increased end-to-end delays and unfair energy consumption among the nodes due to higher packet loss ratio and non-utilization of optimal routes. Various nodes’ stimulation techniques have been proposed. Credit-based incentives with game theoretic approaches are said to be more effective in such experiments. This paper introduces a game theoretic reward-based mechanism to balance the work load among network nodes by stimulating them to equally cooperate in data forwarding toward the base station. Various possible parameters associated with a network and its nodes are considered. In addition, a card-based punishment system is introduced, which is rationally applied on the nodes according to their individual importance in the network. A new technique for finding nodes’ individual importance in the network is designed for better manipulation of nodes.