Survey and taxonomy of packet classification techniques

Author:

Taylor David E.1

Affiliation:

1. Applied Research Laboratory, Washington University in Saint Louis, St. Louis, MO

Abstract

Packet classification is an enabling function for a variety of Internet applications including quality of service, security, monitoring, and multimedia communications. In order to classify a packet as belonging to a particular flow or set of flows, network nodes must perform a search over a set of filters using multiple fields of the packet as the search key. In general, there have been two major threads of research addressing packet classification, algorithmic and architectural. A few pioneering groups of researchers posed the problem, provided complexity bounds, and offered a collection of algorithmic solutions. Subsequently, the design space has been vigorously explored by many offering new algorithms and improvements on existing algorithms. Given the inability of early algorithms to meet performance constraints imposed by high speed links, researchers in industry and academia devised architectural solutions to the problem. This thread of research produced the most widely-used packet classification device technology, Ternary Content Addressable Memory (TCAM). New architectural research combines intelligent algorithms and novel architectures to eliminate many of the unfavorable characteristics of current TCAMs. We observe that the community appears to be converging on a combined algorithmic and architectural approach to the problem. Using a taxonomy based on the high-level approach to the problem and a minimal set of running examples, we provide a survey of the seminal and recent solutions to the problem. It is our hope to foster a deeper understanding of the various packet classification techniques while providing a useful framework for discerning relationships and distinctions.

Publisher

Association for Computing Machinery (ACM)

Subject

General Computer Science,Theoretical Computer Science

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