Trace-based analysis and prediction of cloud computing user behavior using the fractal modeling technique

Shuang Chen, Mahboobeh Ghorbani, Yanzhi Wang, Paul Bogdan, Massoud Pedram

Research output: Chapter in Book/Report/Conference proceedingConference contribution

16 Scopus citations

Abstract

The problem of big data analytics is gaining increasing research interest because of the rapid growth in the volume of data to be analyzed in various areas of science and technology. In this paper, we investigate the characteristics of the cloud computing requests received by the cloud infrastructure operators. The cluster usage dataset released by Google is thoroughly studied. To address the self-similarity and non-stationarity characteristics of the workload profile in a cloud computing system, fractal modeling techniques similar to some cyber-physical system (CPS) applications are exploited. A trace-based prediction of the job inter-arrival time and aggregated resource request sent to server cluster in the near future is effectively performed by solving fractional-order differential equations. The distributions of important parameters including job/task duration time and resource request per task in terms of CPU, memory, and storage are extracted from the cluster dataset are fitted using the alpha-stable distribution.

Original languageEnglish (US)
Title of host publicationProceedings - 2014 IEEE International Congress on Big Data, BigData Congress 2014
EditorsPeter Chen, Peter Chen, Hemant Jain
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages733-739
Number of pages7
ISBN (Electronic)9781479950577
DOIs
StatePublished - Sep 22 2014
Event3rd IEEE International Congress on Big Data, BigData Congress 2014 - Anchorage, United States
Duration: Jun 27 2014Jul 2 2014

Publication series

NameProceedings - 2014 IEEE International Congress on Big Data, BigData Congress 2014

Other

Other3rd IEEE International Congress on Big Data, BigData Congress 2014
CountryUnited States
CityAnchorage
Period6/27/147/2/14

Keywords

  • Google cluster dataset
  • alpha-stable distribution
  • cloud computing
  • fractional order calculus

ASJC Scopus subject areas

  • Computer Science Applications

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