Fair Scheduling in Networks Through Packet Election

TL;DR

This paper introduces a packet-based fairness scheduling algorithm for constrained queuing networks, inspired by election theory, which is proven to be throughput optimal and applicable to various network scenarios.

Contribution

It proposes a novel packet-based fairness notion using election analogy and develops a throughput optimal scheduling algorithm based on this concept.

Findings

The algorithm achieves packet-based fairness in constrained networks.

The scheduling method is throughput optimal.

The approach extends to multiple network scenarios like switches and wireless networks.

Abstract

We consider the problem of designing a fair scheduling algorithm for discrete-time constrained queuing networks. Each queue has dedicated exogenous packet arrivals. There are constraints on which queues can be served simultaneously. This model effectively describes important special instances like network switches, interference in wireless networks, bandwidth sharing for congestion control and traffic scheduling in road roundabouts. Fair scheduling is required because it provides isolation to different traffic flows; isolation makes the system more robust and enables providing quality of service. Existing work on fairness for constrained networks concentrates on flow based fairness. As a main result, we describe a notion of packet based fairness by establishing an analogy with the ranked election problem: packets are voters, schedules are candidates and each packet ranks the schedules based on its priorities. We then obtain a scheduling algorithm that achieves the described notion of fairness by drawing upon the seminal work of Goodman and Markowitz (1952). This yields the familiar Maximum Weight (MW) style algorithm. As another important result we prove that algorithm obtained is throughput optimal. There is no reason a priori why this should be true, and the proof requires non-traditional methods.