The interest in data collected passively, measurement and analysis of traffic has increased tremendously and provides us with new ways to understand, operate and improve Networks performance. The heterogeneity of the Internet is constantly increasing, with new access technologies, new client devices and with more and more services and applications. On the other hand, the interest for the research community to measure enterprise performance has grown, due to a complexity that sometimes rivals Internet.
Then, we propose and validate a method that drills down into the data transfer of each well-behaved connection. The Data time break-down approach automatically extracts the application, access, server and client behavior impacts.
We focus on the issue of profiling anomalous TCP connections that are defined as functionally correct TCP connection but with abnormal performance. Our method enables to pinpoint the root cause of the performance problem, which can be either losses or some idle times during data preparation or transfer.