Distributed Evolution of Strategies in a Game Theoretic Trust Model for Mobile Ad Hoc Networks

Cooperation among nodes is fundamental for the operation of mobile ad hoc networks (MANETs). However, in these networks there could be selfish nodes that use resources from other nodes to send their packets but do not offer their resources to forward packets for other nodes. Several trust models have been proposed as mechanisms to incentive cooperation in MANETs. Some of them are based on game theory concepts. Among game theoretic trust models, those that make nodes’ strategies evolve genetically have shown promising results for cooperation improvement. However, current approaches propose a highly centralized genetic evolution so they cannot properly adapt to fast changing conditions. In this paper, we propose a game theoretic trust model that uses a bacterial-like algorithm to let the nodes quickly learn the appropriate cooperation behavior. Our model is completely distributed and achieves good cooperation values in a small fraction of the time compared with centralized algorithms. Keyword—MANET, Trust models, Game theory, evolutionary algorithm