Global QoS Policy Optimization in SD-WAN

TL;DR

This paper introduces a dynamic QoS policy optimization model for SD-WAN that adjusts application rate limits based on real-time network conditions, significantly improving SLA satisfaction.

Contribution

It presents a novel cross-traffic estimator and two local search algorithms for dynamic QoS tuning in SD-WAN, enhancing network performance.

Findings

40% improvement in SLA satisfaction with adaptive policies

Effective cross-traffic estimation using existing measurements

Significant performance gains demonstrated in packet-level simulations

Abstract

In modern SD-WAN networks, a global controller is able to steer traffic on different paths based on application requirements and global intents. However, existing solutions cannot dynamically tune the way bandwidth is shared between flows inside each overlay link, in particular when the available capacity is uncertain due to cross traffic. In this context, we propose a global QoS (Quality of Service) policy optimization model that dynamically adjusts rate limits of applications based on their requirements to follow the evolution of network conditions. It relies on a novel cross-traffic estimator for the available bandwidth of overlay links that only exploits already available measurements. We propose two local search algorithms, one centralized and one distributed, that leverage cross-traffic estimation. We show in packet-level simulations a significant performance improvement in terms of SLA (Service Level Agreement) satisfaction. For instance, the adaptive tuning of load balancing and QoS policies based on cross-traffic estimation can improve SLA satisfaction by $40\%$ compared to static policies.