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Multi-core Implementation of Decomposition-Based Packet Classification Algorithms

  • Shijie Zhou
  • Yun R. Qu
  • Viktor K. Prasanna
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7979)

Abstract

Multi-field packet classification is a network kernel function where packets are classified based on a set of predefined rules. Many algorithms and hardware architectures have been proposed to accelerate packet classification. Among them, decomposition-based classification approaches are of major interest to the research community because of the parallel search in each packet header field. This paper presents four decomposition-based approaches on multi-core processors. We search in parallel for all the fields using linear search or range-tree search; we store the partial results in a linked list or a bit vector. The partial results are merged to produce the final packet header match. We evaluate the performance with respect to latency and throughput varying the rule set size (1K ~ 64K) and the number of threads per core (1 ~ 12). Experimental results show that our approaches can achieve 128 ns processing latency per packet and 11.5 Gbps overall throughput on state-of-the-art 16-core platforms.

Keywords

Software Define Networking Packet Head Linear Search Incoming Packet Unique Rule 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Shijie Zhou
    • 1
  • Yun R. Qu
    • 1
  • Viktor K. Prasanna
    • 1
  1. 1.Ming Hsieh Department of Electrical EngineeringUniversity of Southern CaliforniaLos AngelesU.S.A.

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