Fast packet classification on OpenFlow switches using multiple R*-tree based bitmap intersection

Ding-Fong Huang, Chien Chen, Mahadevan Thanavel
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引用次数: 1

Abstract

In order to accomplish a stringent speed requirement for processing internet services such as Access Control List (ACL), Quality of Service (QoS), firewalls, etc., software based OpenFlow switches must have a fast packet classification capability. Even for hardware based OpenFlow switches, a limited size of Ternary Content Addressable Memory (TCAM) in the switch could be only enough for a forwarding table. Therefore, ACL, firewall tables, etc. need to be implemented by using the memory of the switch CPU. However, it has become a great challenge to build extremely effectively for next-generation software based packet classification that supports higher throughput and larger flow entries in OpenFlow switch. This paper first exploits a fast packet classification algorithm that forms a R*-Tree based Bitmap Intersection and secondly discusses an enhanced R*-Tree based Bitmap Intersection by using Bloom Filter and Multiple R*-Tree. The evaluation results show that the performance of the algorithm in OpenFlow switches is 4.42 times of Bitmap Intersection and 5.16 times of R*-Tree algorithm and consumes only 300 KB of memory space, which is much less than that of other methods. Finally, the use of multiple R*-Trees has further improved memory usage by about 30%.
基于多R*树的位图交集的OpenFlow交换机快速分组分类
为了满足处理诸如访问控制列表(ACL)、服务质量(QoS)、防火墙等互联网服务的严格速度要求,基于软件的OpenFlow交换机必须具有快速的数据包分类能力。即使对于基于硬件的OpenFlow交换机,交换机中有限大小的三元内容可寻址内存(TCAM)也只能容纳一个转发表。因此,ACL、防火墙表等需要使用交换机CPU的内存来实现。然而,如何在OpenFlow交换机中高效地构建支持更高吞吐量和更大流项的下一代基于软件的数据包分类已经成为一个巨大的挑战。本文首先提出了一种基于R*树的位图交集的快速分组分类算法,然后利用Bloom Filter和Multiple R*树讨论了基于R*树的位图交集的增强算法。评估结果表明,该算法在OpenFlow交换机中的性能是Bitmap Intersection算法的4.42倍、R*-Tree算法的5.16倍,且仅消耗300 KB的内存空间,远远小于其他方法。最后,使用多个R*- tree进一步提高了约30%的内存使用。
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