Machaka, Pheeha and Mabande, Takudzwa and Bagula, Antoine (2011) Monitoring of a Large Wi-Fi Hotspots Network: Performance Investigation of Soft Computing Techniques, Proceedings of Bionetics 2011, 5-6 December 2011, York, England, Springer.
Full text not available from this repository. (Use alternate locations listed below)Abstract
This paper addresses the problem of network monitoring by investigating the performance of three soft computing techniques, the Artificial Neural Network, Bayesian Network and the Artificial Immune System. The techniques were used for achieving situation recognition and monitoring in a large network of Wi-Fi hotspots as part of a highly scalable preemptive monitoring tool for wireless networks. Using a set of data extracted from a live network of Wi-Fi hotspots managed by an ISP, we integrated algorithms into a data collection system to detect anomalous performance and aberrant behavior in the ISP’s network. The results are therefore revealed and discussed in terms of both anomaly performance and aberrant behavior on several test case scenarios.
Item Type: | Conference paper |
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Uncontrolled Keywords: | Performance Monitoring, Neural Networks, Artificial Immune Systems, Bayesian Networks, Anomaly Detection |
Subjects: | Computer systems organization > Architectures > Distributed architectures |
Date Deposited: | 18 Nov 2011 |
Last Modified: | 10 Oct 2019 15:33 |
URI: | http://pubs.cs.uct.ac.za/id/eprint/729 |
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