Approaching Throughput-optimality in Distributed CSMA Scheduling Algorithms with Collisions

TL;DR

This paper develops a Markov chain model for practical CSMA algorithms with collisions, providing throughput formulas and control algorithms to approach optimal throughput in wireless networks.

Contribution

It introduces a new Markov chain model accounting for collisions, and proposes transmission-length control algorithms for near throughput optimality.

Findings

Derived explicit throughput formula considering collisions and overhead.

Proposed control algorithms with proven convergence and stability.

Characterized the relationship between CSMA parameters and capacity region.

Abstract

It was shown recently that CSMA (Carrier Sense Multiple Access)-like distributed algorithms can achieve the maximal throughput in wireless networks (and task processing networks) under certain assumptions. One important, but idealized assumption is that the sensing time is negligible, so that there is no collision. In this paper, we study more practical CSMA-based scheduling algorithms with collisions. First, we provide a Markov chain model and give an explicit throughput formula which takes into account the cost of collisions and overhead. The formula has a simple form since the Markov chain is "almost" time-reversible. Second, we propose transmission-length control algorithms to approach throughput optimality in this case. Sufficient conditions are given to ensure the convergence and stability of the proposed algorithms. Finally, we characterize the relationship between the CSMA parameters (such as the maximum packet lengths) and the achievable capacity region.