Intelligent Automated Diagnosis of Client Device Bottlenecks in Private Clouds
| Autor: | Yasar Ahmet Sekercioglu, M. Ivanovich, Chathuranga Widanapathirana, P. Fitzpatrick, Jonathan C. Li |
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| Rok vydání: | 2012 |
| Předmět: |
Computer Science - Networking and Internet Architecture
Networking and Internet Architecture (cs.NI) FOS: Computer and information sciences Artificial Intelligence (cs.AI) Transmission Control Protocol Computer science Network packet business.industry Computer Science - Artificial Intelligence Real-time computing Cloud computing business Fault (power engineering) |
| DOI: | 10.48550/arxiv.1204.5805 |
| Popis: | 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%. Comment: 2011 Fourth IEEE International Conference on Utility and Cloud Computing (UCC) |
| Databáze: | OpenAIRE |
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