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Research Article | Open Access |

Traffic Classification – Packet-, Flow-, and Application-based Approaches

Author 1: Sasan Adibi
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 1, No. 1 · Published 2010 · Cited by 12

DOI: 10.14569/IJACSA.2010.010102

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Abstract

Traffic classification is a very important mathematical and statistical tool in communications and computer networking, which is used to find average and statistical information of the traffic passing through certain pipe or hub. The results achieved from a proper deployment of a traffic analysis method provide valuable insights, including: how busy a link is, the average end-toend delays, and the average packet size. These valuable information bits will help engineers to design robust networks, avoid possible congestions, and foresee future growth. This paper is designed to capture the essence of traffic classification methods and consider them in packet-, flow-, and application-based contexts.

Keywords

Traffic Classification Packet Flow Applications Delay Payload Size.

How to Cite this Article

Adibi, S. (2010). Traffic Classification – Packet-, Flow-, and Application-based Approaches. International Journal of Advanced Computer Science and Applications, 1(1). https://doi.org/10.14569/IJACSA.2010.010102

Adibi, Sasan. "Traffic Classification – Packet-, Flow-, and Application-based Approaches." International Journal of Advanced Computer Science and Applications, vol. 1, no. 1, 2010, https://doi.org/10.14569/IJACSA.2010.010102.

@article{Adibi2010,
  title     = {Traffic Classification – Packet-, Flow-, and Application-based Approaches},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {1},
  number    = {1},
  year      = {2010},
  publisher = {The Science and Information Organization},
  author    = {Sasan Adibi},
  doi       = {10.14569/IJACSA.2010.010102},
  url       = {https://doi.org/10.14569/IJACSA.2010.010102}
}

Open Access — licensed under a Creative Commons Attribution 4.0 International License. Unrestricted use, distribution, and reproduction in any medium, even commercially, as long as the original work is properly cited.

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Volume 17 No. 11, November 2026
Paper Submission Due October 25, 2026
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