1 research outputs found
Diagnosing client faults using SVM-based intelligent inference from TCP packet traces
We present the Intelligent Automated Client Diagnostic (IACD) system, which
only relies on inference from Transmission Control Protocol (TCP) packet traces
for rapid diagnosis of client device problems that cause network performance
issues. Using soft-margin Support Vector Machine (SVM) classifiers, the system
(i) distinguishes link problems from client problems, and (ii) identifies
characteristics unique to client faults to report the root cause of the client
device problem. Experimental evaluation demonstrated the capability of the IACD
system to distinguish between faulty and healthy links and to diagnose the
client faults with 98% accuracy in healthy links. The system can perform fault
diagnosis independent of the client's specific TCP implementation, enabling
diagnosis capability on diverse range of client computers.Comment: 2011 6th International Conference on Broadband and Biomedical
Communications (IB2COM