Intent-Based Routing Policy Optimization in SD-WAN

• Published in: ICC 2022 - IEEE International Conference on Communications pp. 4914 - 4919
• Main Authors: Anh Quang, Pham Tran, Martin, Sebastien, Leguay, Jeremie, Gong, Xu, Huiying, Xu
• Format: Conference Proceeding
• Language: English
• Published: IEEE 16.05.2022
• Subjects: Minimization; Packet loss; Prediction algorithms; Predictive models; Quality of service; Routing; Wide area networks
• ISSN: 1938-1883
• DOI: 10.1109/ICC45855.2022.9838293

To optimize bandwidth utilization in wide area networks, a centralized controller typically maintains routing policies at edge routers. In this context, we propose a versatile intent-based policy optimization model that carefully selects the set of overlay links which are allowed for applications based on their requirements and the overall intents of the operator. The optimization model embeds QoS and traffic predictions to anticipate the impact of routing decisions. To address large scale scenarios where the behavior of the network and devices is not known exactly, we integrate data-driven predictions into a local search algorithm to optimize routing policies. The algorithm supports several intents such as the minimization of the congestion or the maximization of the network quality. Thanks to packet-level simulations on an SD-WAN scenario, we show that our intent-based policy optimization system improves significantly performances. For instance, the latency is improved by 40% when the high-quality intent is selected. In addition, the percentage of time SLAs are met is improved by 10% compared to legacy load balancing mechanisms.