A cognitive framework for performance/resilience optimized multipath routing in networks with unstable topologies

This paper proposes a framework for optimized multipath routing in a wireless network with frequently changing topology. The topology changes may be due to node mobility in mobile ad hoc networks, or limited node reliability and power supply in sensor networks. The framework attempts to minimize losses (regrets) resulted from uncertainty in the network state at the point of making the routing decision. This uncertainty results from delays in propagating rapidly changing network state information and high cost of network state updates in terms of the network resources. The framework yields the optimal route mixture in the neighborhood of the "best" route. This is consistent with observation [1] that while a desirable goal is to deliver data along the best available (primary) route, maintaining multiple routes through multipath may have beneficial effect on the network performance due to keeping track of the "best" route. The proposed framework explicitly accounts for this effect by assuming that the routing affects the level of uncertainty. Resiliency of the routing under uncertainty may be achieved by assuming that the uncertainty is adversarial, given the available information on the network state. This framework naturally allows for the game theoretic interpretation with routing algorithm making a feasible routing decision and adversarial environment selecting a feasible, i.e., consistent with available information, network state. The optimal route mixture is identified with (generally mixed) Nash routing strategy in the corresponding game. Future efforts should be directed towards solving the corresponding games.