Fabio Ricciato & Marco Mellia 
Traffic Monitoring and Analysis 
Second International Workshop, TMA 2010, Zurich, Switzerland, April 7, 2010. Proceedings

The Second International Workshop on Traffic Monitoring and Analysis (TMA 2010) was an initiative of the COST Action IC0703 ‘Data Traffic Monitoring and Analysis: Theory, Techniques, Tools and Applications for the Future Networks’ (http:// www.tma-portal.eu/cost-tma-action). The COST program is an intergovernmental framework for European cooperation in science and technology, promoting the coordination of nationally funded research on a European level. Each COST Action aims at reducing the fragmentation in – search and opening the European research area to cooperation worldwide. Traffic monitoring and analysis (TMA) is nowadays an important research topic within the field of computer networks. It involves many research groups worldwide that are collectively advancing our understanding of the Internet. The importance of TMA research is motivated by the fact that modern packet n- works are highly complex and ever-evolving objects. Understanding, developing and managing such environments is difficult and expensive in practice. Traffic monitoring is a key methodology for understanding telecommunication technology and improving its operation, and the recent advances in this field suggest that evolved TMA-based techniques can play a key role in the operation of real networks.

Table of Content

Analysis of Internet Datasets.- Understanding and Preparing for DNS Evolution.- Characterizing Traffic Flows Originating from Large-Scale Video Sharing Services.- Mixing Biases: Structural Changes in the AS Topology Evolution.- Tools for Traffic Analysis and Monitoring.- Em Path: Tool to Emulate Packet Transfer Characteristics in IP Network.- A Database of Anomalous Traffic for Assessing Profile Based IDS.- Collection and Exploration of Large Data Monitoring Sets Using Bitmap Databases.- De SRTO: An Effective Algorithm for SRTO Detection in TCP Connections.- Traffic Classification.- Uncovering Relations between Traffic Classifiers and Anomaly Detectors via Graph Theory.- Kiss to Abacus: A Comparison of P2P-TV Traffic Classifiers.- TCP Traffic Classification Using Markov Models.- K-Dimensional Trees for Continuous Traffic Classification.- Performance Measurements.- Validation and Improvement of the Lossy Difference Aggregator to Measure Packet Delays.- End-to-End Available Bandwidth Estimation Tools, An Experimental Comparison.- On the Use of TCP Passive Measurements for Anomaly Detection: A Case Study from an Operational 3G Network.