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首页> 外文期刊>IEEE/ACM Transactions on Networking >Delayed Installation and Expedited Eviction: An Alternative Approach to Reduce Flow Table Occupancy in SDN Switches
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Delayed Installation and Expedited Eviction: An Alternative Approach to Reduce Flow Table Occupancy in SDN Switches

机译：延迟安装和快速驱逐：降低SDN交换机中流表占用率的另一种方法

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摘要

Limited flow table size in switches is a major concern for SDN applications. The common approach to overcome this problem is to identify elephant flows and solely focus on them. However, there is no gold standard to assess the effectiveness of such greedy solutions. In this paper, we formally define this problem by choosing a cost function (hit ratio) and an objective function to optimize the (average table occupancy) and present the optimum solution (i.e., theoretical gold standard) for it. We model the problem as a knapsack problem, analyze how its solution minimizes the table occupancy, and the similarities to and differences from the default idle timeout mechanism used in OpenFlow. We also present a new approach to minimize flow table occupancy based on the insight gained from the knapsack model analysis. Our solution expedites rule evictions by forecasting the TCP flow termination from RST/FIN packets and delays rule installation by incubating non-TCP flows. It reduces average flow table occupancy between 16%-62% in various networks with less than 1.5% reduction in hit ratio. Using three real-world packet traces, we compare the performance of our solution with the theoretically optimum solution, the static idle timeout approach used in current OpenFlow systems, and heavy hitter detection approaches that are commonly used to solve this problem. We provide in-depth analysis of when and where our approach outperforms other solutions, while discussing why it might be better to use rate-based heavy hitter detection in some scenarios.
机译：交换机中有限的流表大小是SDN应用程序的主要问题。解决此问题的常用方法是识别大象流，并仅关注它们。但是，没有金标准来评估这种贪婪解决方案的有效性。在本文中，我们通过选择成本函数（命中率）和目标函数来优化（平均餐桌占用率）并为此提出最优解决方案（即理论金标准）来正式定义此问题。我们将问题建模为背包问题，分析其解决方案如何最大程度地减少表占用率，以及与OpenFlow中使用的默认空闲超时机制的异同。我们还基于从背包模型分析中获得的见识，提出了一种最小化流表占用率的新方法。我们的解决方案通过从RST / FIN数据包预测TCP流终止来加快规则逐出，并通过孵化非TCP流来延迟规则安装。它将各种网络中的平均流表占用率降低了16％-62％，命中率降低了不到1.5％。使用三个实际的数据包跟踪，我们将解决方案的性能与理论上最佳的解决方案，当前OpenFlow系统中使用的静态空闲超时方法以及通常用于解决此问题的沉重击球手检测方法进行了比较。我们提供了何时何地我们的方法优于其他解决方案的深入分析，同时讨论了为什么在某些情况下使用基于比率的重击球手检测可能会更好。

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