An efficient flow cache algorithm with improved fairness in Software-Defined Data Center Networks

Bu-Sung Lee, Renuga Kanagavelu, Khin Mi Mi Aung
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引用次数: 46

Abstract

The use of Software-Defined Networking (SDN) with OpenFlow-enabled switches in Data Centers has received much attention from researchers and industries. One of the major issues in OpenFlow switch is the limited size of the flow table resulting in evictions of flows from the flow table. From Data Center traffic characteristics, we observe that elephant flows are very large in size (data volume) but few in numbers when compared to mice flows. Thus, Elephant flows are more likely to be evicted, due to the limited size of the switch flow table causing additional traffic to the controller. We propose a differential flow cache framework that achieves fairness and efficient cache maintenance with fast lookup and reduced cache miss ratio. The framework uses a hash-based placement and localized Least Recently Used (LRU)-based replacement mechanisms.
软件定义数据中心网络中一种提高公平性的高效流缓存算法
在数据中心中使用软件定义网络(SDN)和openflow交换机已经受到了研究人员和工业界的广泛关注。OpenFlow开关的一个主要问题是流表的大小有限,导致从流表中驱逐流。从数据中心流量特征来看,我们观察到大象流的规模(数据量)非常大,但与老鼠流相比,大象流的数量很少。因此,大象流更有可能被驱逐,因为交换机流表的大小有限,会给控制器带来额外的流量。我们提出了一种差分流缓存框架,该框架通过快速查找和降低缓存丢失率来实现公平和高效的缓存维护。该框架使用基于散列的放置和基于本地化的最近最少使用(Least Recently Used, LRU)的替换机制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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