Intelligent Automated Diagnosis of Client Device Bottlenecks in Private Clouds

TL;DR

This paper introduces IACD, an automated system that diagnoses client device issues in private clouds using TCP packet traces and SVM classifiers, achieving 98% accuracy.

Contribution

The paper presents a modular, extendible diagnostic system that accurately detects client device faults in private clouds regardless of TCP variants.

Findings

Achieved 98% diagnostic accuracy in controlled experiments.

System is extendible to new faults and TCP variants.

Uses TCP packet trace analysis and SVM classifiers.

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%.