Convexity and Optimization in Deficit Round Robin Scheduling for Delay-Constrained Systems
Abstract
The Deficit Round Robin (DRR) scheduler is widely used in network systems for its simplicity and fairness. However, configuring its integer-valued parameters, known as quanta, to meet stringent delay constraints remains a significant challenge. This paper addresses this issue by demonstrating the convexity of the feasible parameter set for a two-flow DRR system under delay constraints. The analysis is then extended to n-flow systems, uncovering key structural properties that guide parameter selection. Additionally, we propose an optimization method to maximize the number of packets served in a round while satisfying delay constraints. The effectiveness of this approach is validated through numerical simulations, providing a practical framework for enhancing DRR scheduling. These findings offer valuable insights into resource allocation strategies for maintaining Quality of Service (QoS) standards in network slicing environments.
Keywords
Cite
@article{arxiv.2503.23366,
title = {Convexity and Optimization in Deficit Round Robin Scheduling for Delay-Constrained Systems},
author = {Aniket Mukherjee and Joy Kuri and Chandramani Singh},
journal= {arXiv preprint arXiv:2503.23366},
year = {2025}
}