Traffic Classification over Gbit Speed with Commodity Hardware
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
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
G. Szabo, I. Godor, A. Veres, S. Malomsoky and S. Molnar, "Traffic Classification over Gbit Speed with Commodity Hardware," in Journal of Communications Software and Systems, vol. 5, no. 3, pp. 93-100, September 2009, doi: 10.24138/jcomss.v5i3.203
@article{szabo2009trafficclassification,
author = {Geza Szabo and Istvan Godor and Andras Veres and Szabolcs Malomsoky and Sandor Molnar},
title = {Traffic Classification over Gbit Speed with Commodity Hardware},
journal = {Journal of Communications Software and Systems},
month = {9},
year = {2009},
volume = {5},
number = {3},
pages = {93--100},
doi = {10.24138/jcomss.v5i3.203},
url = {https://doi.org/10.24138/jcomss.v5i3.203}
}