Multi-Path Alpha-Fair Resource Allocation at Scale in Distributed Software Defined Networks

TL;DR

This paper introduces a distributed ADMM-based algorithm for multi-path fair resource allocation in large-scale SDN networks, ensuring convergence to fair solutions while maintaining feasibility and scalability.

Contribution

The paper presents a novel distributed ADMM algorithm for multi-path fair resource allocation in SDN, capable of handling large-scale networks efficiently.

Findings

Algorithm converges to fair resource allocation

Handles large-scale network instances effectively

Maintains feasibility throughout the process

Abstract

The performance of computer networks relies on how bandwidth is shared among different flows. Fair resource allocation is a challenging problem particularly when the flows evolve over time. To address this issue, bandwidth sharing techniques that quickly react to the traffic fluctuations are of interest, especially in large scale settings with hundreds of nodes and thousands of flows. In this context, we propose a distributed algorithm based on the Alternating Direction Method of Multipliers (ADMM) that tackles the multi-path fair resource allocation problem in a distributed SDN control architecture. Our ADMM-based algorithm continuously generates a sequence of resource allocation solutions converging to the fair allocation while always remaining feasible, a property that standard primal-dual decomposition methods often lack. Thanks to the distribution of all computer intensive operations, we demonstrate that we can handle large instances at scale.