Quality of service statistics over heterogeneous networks: Analysis and applications

Heterogeneous wireless/wired networks and ubiquitous environments are gaining ever more attention by research community. To properly control and manage such puzzles a deep knowledge of quality of service parameters is needed and, therefore, a complete and robust performance assessment is necessary. This paper deals with a performance evaluation and measurement of a number of heterogeneous end-to-end paths taking into account a wide range of statistics. To study the behavior of QoS parameters, an active measurement approach has been introduced for the analysis of properties we called (i) concise statistics (mean, standard deviation, inter quantile range, minimum, maximum, and median) and (ii) detailed statistics (Probability Density Function, Auto-correlation Function, Entropy, Complementary Cumulative Distribution Function, and Bivariate Probability Density Function). We show how, thanks to this view on QoS statistics, a more complete understanding of QoS parameters behavior is possible. In addition, we show how the measured statistics can be fruitfully used in the context of network control and management. More precisely, we present two proof of concepts regarding frameworks for QoS-based anomaly detection and for QoS-based identification of network elements.