Node-based Service-Balanced Scheduling for Provably Guaranteed Throughput and Evacuation Time Performance

TL;DR

This paper introduces a novel node-based scheduling algorithm for multi-hop wireless networks that guarantees near-optimal throughput and evacuation time, improving upon prior link-based methods with proven performance bounds.

Contribution

The paper proposes the NSB algorithm that balances node congestion for improved throughput and evacuation time, with a lower-complexity variant LC-NSB, and provides rigorous theoretical guarantees.

Findings

NSB achieves at least 2/3 efficiency ratio for throughput.

NSB guarantees an evacuation time approximation ratio of at most 3/2.

NSB is optimal for bipartite networks.

Abstract

This paper focuses on the design of provably efficient online link scheduling algorithms for multi-hop wireless networks. We consider single-hop traffic and the one-hop interference model. The objective is twofold: 1) maximizing the throughput when the flow sources continuously inject packets into the network, and 2) minimizing the evacuation time when there are no future packet arrivals. The prior work mostly employs the link-based approach, which leads to throughput-efficient algorithms but often does not guarantee satisfactory evacuation time performance. In this paper, we propose a novel Node-based Service-Balanced (NSB) online scheduling algorithm. NSB aims to give scheduling opportunities to heavily congested nodes in a balanced manner, by maximizing the total weight of the scheduled nodes in each scheduling cycle, where the weight of a node is determined by its workload and whether the node was scheduled in the previous scheduling cycle(s). We rigorously prove that NSB guarantees to achieve an efficiency ratio no worse (or no smaller) than 2/3 for the throughput and an approximation ratio no worse (or no greater) than 3/2 for the evacuation time. It is remarkable that NSB is both throughput-optimal and evacuation-time-optimal if the underlying network graph is bipartite. Further, we develop a lower-complexity NSB algorithm, called LC-NSB, which provides the same performance guarantees as NSB. Finally, we conduct numerical experiments to elucidate our theoretical results.