Evolution of Strategy Driven Behavior in Ad Hoc Networks Using a Genetic Algorithm

In this paper we address the problem of selfish behavior in ad hoc networks. We propose a strategy driven approach which aims at enforcing cooperation between network participants. Each node (player) is using a strategy that defines conditions under which packets are being forwarded. Such strategy is based on the notion of trust and activity of the source node of the packet. This way network participants are enforced to forward packets and to reduce the amount of time of being in a sleep mode. To evaluate strategies we use a new game theory based model of an ad hoc network. This model has some similarities with the iterated prisoner´s dilemma under the random pairing game where randomly chosen players receive payoffs that depend on the way they behave. Our model of the network also includes a simple reputation collection and trust evaluation mechanisms. A genetic algorithm (GA) is applied to find good strategies. Experimental results show that approach can successfully enforce cooperation among ad hoc networks participants.