Throughput-optimal Scheduling in Multi-hop Wireless Networks without Per-flow Information

TL;DR

This paper introduces throughput-optimal link scheduling schemes for multi-hop wireless networks that do not rely on per-flow information, using local or hop-count data to improve delay performance.

Contribution

It proposes novel scheduling schemes that are throughput-optimal without requiring per-flow data, simplifying implementation and reducing delay.

Findings

Proposed schemes are proven to be throughput-optimal using fluid limit analysis.

Simulations show significant delay improvements over traditional back-pressure algorithms.

Schemes operate effectively with only local or hop-count information.

Abstract

In this paper, we consider the problem of link scheduling in multi-hop wireless networks under general interference constraints. Our goal is to design scheduling schemes that do not use per-flow or per-destination information, maintain a single data queue for each link, and exploit only local information, while guaranteeing throughput optimality. Although the celebrated back-pressure algorithm maximizes throughput, it requires per-flow or per-destination information. It is usually difficult to obtain and maintain this type of information, especially in large networks, where there are numerous flows. Also, the back-pressure algorithm maintains a complex data structure at each node, keeps exchanging queue length information among neighboring nodes, and commonly results in poor delay performance. In this paper, we propose scheduling schemes that can circumvent these drawbacks and guarantee throughput optimality. These schemes use either the readily available hop-count information or only the local information for each link. We rigorously analyze the performance of the proposed schemes using fluid limit techniques via an inductive argument and show that they are throughput-optimal. We also conduct simulations to validate our theoretical results in various settings, and show that the proposed schemes can substantially improve the delay performance in most scenarios.