Traffic Classification over Gbit Speed with Commodity Hardware

Published online: Sep 21, 2009
Full Text: PDF (747 KiB)
DOI: 10.24138/jcomss.v5i3.203
Authors:
Geza Szabo, Istvan Godor, Andras Veres, Szabolcs Malomsoky, Sandor Molnar

Abstract

This paper discusses necessary components of a GPU-assisted traffic classification method, which is capable of multi-Gbps speeds on commodity hardware. The majority of the traffic classification is pushed to the GPU to offload the CPU, which then may serve other processing intensive tasks, e.g., traffic capture. The paper presents two massively parallelizable algorithms suitable for GPUs. The first one performs signature search using a modification of Zobrist hashing. The second algorithm supports connection pattern-based analysis and aggregation of matches using a parallel-prefix-sum algorithm adapted to GPU. The performance tests of the proposed methods showed that traffic classification is possible up to approximately 6 Gbps with a commodity PC.

Keywords

traffic classification, GPU, parallel algorithm
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