Traffic Monitoring and Analysis

1. Front Matter

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2. QoS Measurement

   1. Realistic Passive Packet Loss Measurement for High-Speed Networks

      • Aleš Friedl, Sven Ubik, Alexandros Kapravelos, Michalis Polychronakis, Evangelos P. Markatos

      Pages 1-7

   2. Inferring Queue State by Measuring Delay in a WiFi Network

      • David Malone, Douglas J Leith, Ian Dangerfield

      Pages 8-16

   3. Network-Wide Measurements of TCP RTT in 3G

      • Peter Romirer-Maierhofer, Fabio Ricciato, Alessandro D’Alconzo, Robert Franzan, Wolfgang Karner

      Pages 17-25

3. Rupture Detection

   1. Portscan Detection with Sampled NetFlow

      • Ignasi Paredes-Oliva, Pere Barlet-Ros, Josep Solé-Pareta

      Pages 26-33

   2. Automated Detection of Load Changes in Large-Scale Networks

      • Felipe Mata, Javier Aracil, Jose Luis García-Dorado

      Pages 34-41

   3. Passive, Streaming Inference of TCP Connection Structure for Network Server Management

      • Jeff Terrell, Kevin Jeffay, F. Donelson Smith, Jim Gogan, Joni Keller

      Pages 42-53

4. Traffic Classification

   1. GTVS: Boosting the Collection of Application Traffic Ground Truth

      • Marco Canini, Wei Li, Andrew W. Moore, Raffaele Bolla

      Pages 54-63

   2. TIE: A Community-Oriented Traffic Classification Platform

      • Alberto Dainotti, Walter de Donato, Antonio Pescapé

      Pages 64-74

   3. Revealing the Unknown ADSL Traffic Using Statistical Methods

      • Marcin Pietrzyk, Guillaume Urvoy-Keller, Jean-Laurent Costeux

      Pages 75-83

   4. Accurate, Fine-Grained Classification of P2P-TV Applications by Simply Counting Packets

      • Silvio Valenti, Dario Rossi, Michela Meo, Marco Mellia, Paola Bermolen

      Pages 84-92

   5. Detection and Tracking of Skype by Exploiting Cross Layer Information in a Live 3G Network

      • Philipp Svoboda, Esa Hyytiä, Fabio Ricciato, Markus Rupp, Martin Karner

      Pages 93-100

5. Traffic Analysis and Topology Measurements

   1. Incentives for BGP Guided IP-Level Topology Discovery

      • Benoit Donnet

      Pages 101-108

   2. Scaling Analysis of Wavelet Quantiles in Network Traffic

      • Giada Giorgi, Claudio Narduzzi

      Pages 109-116

   3. KISS: Stochastic Packet Inspection

      • Alessandro Finamore, Marco Mellia, Michela Meo, Dario Rossi

      Pages 117-125

   4. DTS: A Decentralized Tracing System

      • Kenji Masui, Benoit Donnet

      Pages 126-134

6. Back Matter

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The First International Workshop on Traffic Monitoring and Analysis (TMA 2009) was an initiative from the COST Action IC0703 "Data Traffic Monitoring and Analysis: Theory, Techniques, Tools and Applications for the Future Networks" (www.cost-tma.eu). The COST program is an intergovernmental framework for European Cooperation in Science and Technology, allowing the coordination of nationally funded research on a European level. Each COST Action contributes to reducing the fragmentation in research and opening the European Research Area to cooperation worldwide. Traffic monitoring and analysis (TMA) is now an important research topic within the field of networking. It involves many research groups worldwide that are coll- tively 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. Moreover, TMA offers a basis for prevention and response in network security, as typically the det- tion of attacks and intrusions requires the analysis of detailed traffic records. On the more theoretical side, TMA is an attractive research topic for many reasons.

• AAC
• Monitoring
• NetFlow
• QoS
• anomaly detection
• autonomous systems
• benchmarks
• capacity planning
• cellular networks
• classification
• dynamic QoS
• dynamic networks
• mobile networks
• monitor
• tools

• Dept. of Computer Science, F.O.R.T.H., Institute of Computer Science, Vassilika Vouton, P.O. Box 1385, 711 10, Heraklion, Greece, and University of Crete, Heraklion, Greece

  Maria Papadopouli

• LAAS – CNRS, Toulouse, France

  Philippe Owezarski

• Dept. of Electrical Engineering, Mathematics and Computer Science, Design and Analysis of Communication Systems Group, University of Twente, Enschede, The Netherlands

  Aiko Pras

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