Quality of Service analysis of Internet links with minimal information

Monitoring the Quality of Service (QoS) of Internet links is of paramount importance for network managers, and consequently has received great attention from the research community. To monitor QoS, practitioners leverage on network traffic measurements and, by means of practical models and statistical techniques, make predictions and detect outliers that allow the planning of telecommunication networks and detection of abnormal behavior, respectively. However, obtaining detailed measurements from Internet links at current network speeds is very challenging. Moreover, the amount of resources required to properly storage detailed network measurements make unfeasible to perform long measurement campaigns. These facts have motivated the application of techniques to reduce the information gathered from the network, such as sampling or the use of summarized statistics, making network traffic monitoring less demanding and allowing longer measurement campaigns. Accordingly, this thesis proposes two novel methodologies to perform QoS analysis of Internet links leveraging on summarized statistics of network traffic. Each methodology relies on a network traffic model, on which sound statistical methodologies are used on attempts of detecting relevant events that either require action from the network managers or are related with degradations of the provided QoS.