Low-complexity scheduling algorithm for sum-queue minimization in wireless convergecast

We consider the problem of link scheduling for efficient convergecast in a wireless system. While there have been many results on scheduling algorithms that attain the maximum possible throughput in such a system, there have been few results that provide scheduling algorithms that are optimal in terms of some quality-of-service metric such as the probability that the end-to-end buffer usage exceeds a large threshold. Using a large deviations framework, we design a novel and low complexity algorithm that attains the optimal asymptotic decay rate for the overflow probability of the sum-queue (i.e. the total queue backlog in the entire system) as the overflow threshold becomes large. Simulations show that this algorithm has better performance than well known algorithms such as the standard back-pressure algorithm and the multihop version of greedy maximal matching (combined with back-pressure). Our proposed algorithm performs better not only in terms of the asymptotic decay rate at large overflow thresholds, but also in terms of the actual probability of overflow for practical range of overflow thresholds.