On maximizing collaboration in wireless mesh networks without monetary incentives

In distributed network settings, where nodes are not under the control of a single administrative entity, the fulfillment of fundamental network operations is heavily dependent on their cooperation. Nevertheless, individual interests in combination with resource constraints do not always encourage cooperative behavior. In this work, we focus on static Wireless Mesh Networks (WMNs) and address the issue of selfishness in packet forwarding. Firstly, we model the dependencies that emerge in these networks as a result of their topology, traffic demand matrix, and route selection and determine the conditions for the natural emergence of collaboration, without the need of (monetary) incentives. We then assess the achievable collaboration levels, i.e., percentage of traffic demands (flows) that can be served thanks to the emerging collaboration, in both synthetic and real-world WMN topologies under shortest-path routing. Our results show that the cooperation improves when the number of flows increases. Yet, certain topological characteristics (marginal nodes, node degree distributions) make full cooperation difficult to achieve for the average case and bound it asymptotically. Finally, and motivated by these results, we use our dependency model to drive the selection of routes in the network. We cast the routing problem as a mixed-integer programming problem, which tries to maximize the collaboration level in the network. Our study investigates the resulting tradeoff among network throughput, served traffic flows, and routing stretch factor.