Intelligent Automated Diagnosis of Client Device Bottlenecks in Private Clouds

C. Widanapathirana; J. Li; Y. A. Sekercioglu; M. Ivanovich; P. Fitzpatrick

doi:10.1109/UCC.2011.42

Intelligent Automated Diagnosis of Client Device Bottlenecks in Private Clouds

Networking and Internet Architecture 2012-04-27 v1 Artificial Intelligence

Authors: C. Widanapathirana , J. Li , Y. A. Sekercioglu , M. Ivanovich , P. Fitzpatrick

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Abstract

We present an automated solution for rapid diagnosis of client device problems in private cloud environments: the Intelligent Automated Client Diagnostic (IACD) system. Clients are diagnosed with the aid of Transmission Control Protocol (TCP) packet traces, by (i) observation of anomalous artifacts occurring as a result of each fault and (ii) subsequent use of the inference capabilities of soft-margin Support Vector Machine (SVM) classifiers. The IACD system features a modular design and is extendible to new faults, with detection capability unaffected by the TCP variant used at the client. Experimental evaluation of the IACD system in a controlled environment demonstrated an overall diagnostic accuracy of 98%.

Keywords

automated diagnosis client device bottlenecks private clouds TCP packet traces support vector machine fault detection IACD system

Cite

@article{arxiv.1204.5805,
  title  = {Intelligent Automated Diagnosis of Client Device Bottlenecks in Private Clouds},
  author = {C. Widanapathirana and J. Li and Y. A. Sekercioglu and M. Ivanovich and P. Fitzpatrick},
  journal= {arXiv preprint arXiv:1204.5805},
  year   = {2012}
}

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2011 Fourth IEEE International Conference on Utility and Cloud Computing (UCC)

Intelligent Automated Diagnosis of Client Device Bottlenecks in Private Clouds

Abstract

Keywords

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