OpenFlow多表查找的内存成本分析

K. G. Perez, Sandra Scott-Hayward, Xin Yang, S. Sezer
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引用次数: 3

摘要

软件定义网络(SDN)中的多个表查找架构为令人兴奋的新网络应用打开了大门。OpenFlow协议的开发支持SDN范式。然而,OpenFlow协议的第一个版本指定了一个单一的表查找模型,在流条目数和搜索能力方面有相关的约束。随着OpenFlow v1.1中多表查找的引入,支持SDN应用创新的灵活高效的搜索成为可能。然而,在硬件中实现多表查找以满足高性能要求并非易事。一种可能的方法涉及使用多维查找算法。通过使用嵌入式内存作为流入口存储,可以获得较高的查找性能。本文对OpenFlow的多维查找流过滤器进行了详细的研究。基于提出的多表查找架构,评估了使用并行单字段搜索的内存消耗和更新性能。结果展示了一种高效的多表查找实现,内存使用最少。
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Memory cost analysis for OpenFlow multiple table lookup
Multiple Table Lookup architectures in Software Defined Networking (SDN) open the door for exciting new network applications. The development of the OpenFlow protocol supported the SDN paradigm. However, the first version of the OpenFlow protocol specified a single table lookup model with the associated constraints in flow entry numbers and search capabilities. With the introduction of multiple table lookup in OpenFlow v1.1, flexible and efficient search to support SDN application innovation became possible. However, implementation of multiple table lookup in hardware to meet high performance requirements is non-trivial. One possible approach involves the use of multi-dimensional lookup algorithms. A high lookup performance can be achieved by using embedded memory for flow entry storage. A detailed study of OpenFlow flow filters for multi-dimensional lookup is presented in this paper. Based on a proposed multiple table lookup architecture, the memory consumption and update performance using parallel single field searches are evaluated. The results demonstrate an efficient multi-table lookup implementation with minimum memory usage.
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