Pham Tran Anh Quang, Jérémie Leguay, Xuan Gong, Huiying Xu
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引用次数: 0
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 network, 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 a centralized local search algorithm with cross-traffic estimation and show in packet-level simulations a significant performance improvement in terms of SLA (Service Level Agreement) satisfaction. The adaptive tuning of load balancing and QoS policies based on cross-traffic estimation can improve SLA satisfaction by 40% compared to static policies.
在现代SD-WAN网络中,全局控制器能够根据应用程序需求和全局意图引导不同路径上的流量。然而,现有的解决方案不能动态地调整每个网络中的流之间共享带宽的方式,特别是当可用容量由于交叉流量而不确定时。在此背景下,我们提出了一种全局QoS (Quality of Service)策略优化模型,该模型可以根据应用的需求动态调整速率限制,以适应网络条件的演变。它依赖于一种新的交叉流量估计器,用于覆盖链路的可用带宽,该估计器仅利用已有的测量值。我们提出了一种具有交叉流量估计的集中式本地搜索算法,并在分组级模拟中显示了SLA(服务水平协议)满意度方面的显着性能改进。与静态策略相比,基于交叉流量估计的负载平衡和QoS策略的自适应调优可以将SLA满意度提高40%。