A Bayesian Game Based Optimization Strategy Proposal for Routing in Energy Constrained DTNs

In this paper, we propose an optimization strategy to be applied to a well-known DTN routing algorithm as PRoPHET and SimBetTS which, by default, don't regard to the issue of energy constraint. Our proposed strategy is based on modeling of the message forwarding as a Bayesian game that aims specifically to capture the dynamic nature of the multi-copy replication decisions, the energy constraint of the nodes and the belief about the energy of other nodes. In addition, we consider factors of evidence aging on accumulated observations used to update the belief that a node has about the energy of the other nodes. The main feature of this belief update system is not to utilize neighborhood watch or acknowledgment mechanism. Moreover, in this paper, we conduct simulation experiments to evaluate the performance of our optimization strategy proposal from a DTN scenario with heterogeneous nodes based on realistic human mobility traces. Simulations results show that our proposed optimization strategy is able to lead the network to remain operational for a longer period of time and, consequently, to achieve a higher final delivery ratio even when compared to a proposal using energy-aware routing.