Data mining techniques for effective and scalable traffic analysis
This paper describes experiments in applying data mining techniques to historical data collected by network monitoring agents. Large amounts of performance data, including network, system, and application performance data, are collected and stored by monitoring agents. Data mining algorithms analyze the data and codify it into usable knowledge. We show, via experiments, that the knowledge contains useful and unexpected suggestions for improving the effectiveness of business processes and for reducing management support effort. Four experiments are discussed: three preliminary lab experiments and one large, real-world experiment at a major airline company.