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Fast Lookup Is Not Enough: Towards Efficient and Scalable Flow Entry Updates for TCAM-Based OpenFlow Switches

机译:快速查找还不够:针对基于TCAM的OpenFlow交换机的高效且可扩展的流条目更新

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With an increasing demand for flexible management in software-defined networks (SDNs), it becomes critical to minimize the network policy update time. Although major SDN controllers are now optimized for rapid network update at the control plane, there is still room for data plane optimization in terms of update time, when using TCAM-based physical SDN commodity-off-the-shelf switches. A slow update directly affects network performance creating bottlenecks. To minimize flow entry update time, a dependency graph, a kind of DAG (directed acyclic graph), can be used for the access management of flow entries at the switch. Thanks to the DAG, unnecessary entry movements, which are the main factor slowing down flow entry updates, can be avoided. However, existing algorithms show limitations when updates become very frequent. We propose a new flow entry update algorithm, called FastRule, that exploits a greedy strategy with an efficient data structure to accelerate flow entry update with a DAG approach. Moreover, we also adjust our algorithm for other flow table layouts to make it scalable. We elaborate on the correctness of FastRule and test our algorithm using a hardware switch. Compared with existing algorithms, the evaluation shows that our algorithm is about 100x faster than state-of-the-art solutions with a flow table of 1k line size.
机译:随着对软件定义网络(SDN)中的灵活管理的需求不断增加,最小化网络策略更新时间变得至关重要。尽管现在已经对主要的SDN控制器进行了优化,以在控制平面上进行快速的网络更新,但是在使用基于TCAM的物理SDN商品现成交换机时,在更新时间方面仍存在数据平面优化的空间。更新缓慢会直接影响网络性能,从而造成瓶颈。为了最小化流条目更新时间,可以使用一种依赖关系图(一种DAG(有向无环图))来对交换机上的流条目进行访问管理。多亏了DAG,可以避免不必要的入口移动,这是减慢流入口更新的主要因素。但是,现有的算法在更新变得非常频繁时显示出局限性。我们提出了一种新的流条目更新算法,称为FastRule,该算法利用具有有效数据结构的贪婪策略来通过DAG方法加速流条目更新。此外,我们还针对其他流表布局调整了算法,以使其具有可扩展性。我们详细介绍了FastRule的正确性,并使用硬件开关测试了我们的算法。与现有算法相比,评估表明,我们的算法比流表为1k的最新解决方案快约100倍。

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