Winning the Lottery: Learning Perfect Coordination With Minimal Feedback

Coordination is a central problem whenever stations (or nodes or users) share resources across a network. In the absence of coordination, there will be collision, congestion or interference, with concomitant loss of performance. This paper proposes new protocols, which we call perfect coordination (PC) protocols, that solve the coordination problem. PC protocols are completely distributed (requiring neither central control nor the exchange of any control messages), fast (with speeds comparable to those of any existing protocols), fully efficient (achieving perfect coordination, with no collisions and no gaps) and require minimal feedback. PC protocols rely heavily on learning, exploiting the possibility to use both actions and silence as messages and the ability of stations to learn from their own histories while simultaneously enabling the learning of other stations. PC protocols can be formulated as finite automata and implemented using currently existing technology (e.g., wireless cards). Simulations show that, in a variety of deployment scenarios, PC protocols outperform existing state-of-the-art protocols-despite requiring much less feedback.