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.
翻译:在现代SD-WAN网络中,全局控制器可以根据应用程序的要求和全局意图引导流量走不同的路径。然而,现有解决方案无法在每个覆盖链接内动态调整流之间带宽共享的方式,特别是当可用容量由于交叉流量而不确定时。在这种情况下,我们提出了一种全局QoS(服务质量)策略优化模型,它基于应用程序的需求动态调整速率限制,以便跟随网络条件的变化。它依赖于一种新颖的交叉流量估计器,用于估算覆盖链接的可用带宽,该估计器仅利用已有的测量数据。我们提出了两种本地搜索算法,一种是集中的,一种是分布式的,两种算法均利用了交叉流量估算。我们在数据包级模拟中展示了显著的性能改善,特别是在满足服务级别协议(SLA)方面的表现。例如,基于交叉流量估计的负载均衡和QoS策略的自适应调整可以将SLA满足度提高40%,与静态策略相比。