Towards a Packet Traffic Genome Project as a Method for Realtime Sub-Flow Traffic Analysis

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Abstract

This paper proposes the novel idea of a packet traffic genome where sequence of bursts and gaps between bursts are encoded as a sequence of genes that represents the respective flow in analysis. This paper shows that, while individual flow genomes are too diverse for a valid analysis, the gene soup representing the total current traffic aggregate exhibits repeated patterns. The repetition can be used to reduce optimizational complexity of management decisions-this is when a pre-calculated solution can be used for a repeated pattern. Moreover, this paper shows that the genome concept can be helpful for switching at subflow level (e.g. circuits for individual bursts) and can serve as a visualization tool both at the level of individual flows and total aggregate traffic.

Original languageEnglish
Title of host publicationProceedings - 2018 IEEE 42nd Annual Computer Software and Applications Conference, COMPSAC 2018
EditorsClaudio Demartini, Sorel Reisman, Ling Liu, Edmundo Tovar, Hiroki Takakura, Ji-Jiang Yang, Chung-Horng Lung, Sheikh Iqbal Ahamed, Kamrul Hasan, Thomas Conte, Motonori Nakamura, Zhiyong Zhang, Toyokazu Akiyama, William Claycomb, Stelvio Cimato
PublisherIEEE Computer Society
Pages670-675
Number of pages6
ISBN (Electronic)9781538626665
DOIs
Publication statusPublished - 8 Jun 2018
Event42nd IEEE Computer Software and Applications Conference, COMPSAC 2018 - Tokyo, Japan
Duration: 23 Jul 201827 Jul 2018

Publication series

NameProceedings - International Computer Software and Applications Conference
Volume2
ISSN (Print)0730-3157

Conference

Conference42nd IEEE Computer Software and Applications Conference, COMPSAC 2018
CountryJapan
CityTokyo
Period23/07/1827/07/18

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Keywords

  • Circuit switching
  • Flowlets
  • Optimizational complexity
  • Packet bursts
  • Subflow traffic analysis
  • Traffic visualization

Cite this

Marat, Z. (2018). Towards a Packet Traffic Genome Project as a Method for Realtime Sub-Flow Traffic Analysis. In C. Demartini, S. Reisman, L. Liu, E. Tovar, H. Takakura, J-J. Yang, C-H. Lung, S. I. Ahamed, K. Hasan, T. Conte, M. Nakamura, Z. Zhang, T. Akiyama, W. Claycomb, ... S. Cimato (Eds.), Proceedings - 2018 IEEE 42nd Annual Computer Software and Applications Conference, COMPSAC 2018 (pp. 670-675). [8377944] (Proceedings - International Computer Software and Applications Conference; Vol. 2). IEEE Computer Society. https://doi.org/10.1109/COMPSAC.2018.10316