Robust CSMA: Adapting to channel and traffic asymmetry

It has recently been shown that distributed queue-based adaptation of CSMA´s contention aggressiveness can provably optimize network utility. However, such an approach is fragile, in that it suffers high performance degradation under conditions of asymmetric channels, heterogeneous traffic, and packet collisions. In this work, we address the main sources of performance degradation in optimal CSMA to design a distributed system for proportional-fair throughput that delivers high performance in a wide-range of network conditions. First, we generalize prior optimal CSMA models to incorporate individual per-link modulation and coding rates. With such a model, we derive adaptive principles that maximize utility under arbitrary channel capacities. Second, we propose a novel structure that can be used in the place of queues to provide optimal CSMA adaptation. As such a structure does not use traffic backlog to operate, the resulting adaptation is optimal for the set of backlogged flows under general traffic arrival patterns. Third, we propose a robustness function that reduces access attempts in high contention scenarios to avoid high performance degradation due to collisions. By evaluating our approach in combined scenarios that incorporate the three main sources of performance degradation, we observe vast performance gains, with an average 68% higher logarithmic utility compared to prior solutions.