Network measurement and analysis plays a central role in the design, implementation, management and maintenance of modern and complex telecommunication networks. With the exponential growth of existing networks (e.g., including the Internet, the Web, data-center, social, mobile, cellular, vehicular, sensor and body area networks) and the continued proliferation of new types of services, measurement and analysis is becoming not only a paramount task but also a very challenging one.
Traditional approaches to network measurement and analysis need to be frequently updated to cope with the growth in traffic volume and diversity, as well as to answer to new research questions. For instance, in terms of methodology and technology, Big Data analytics is becoming increasingly relevant (including streaming/batch frameworks, but more generally to all statistical, machine learning or signal processing techniques that can be applied to large volumes of data). In terms of topics, in addition to the classical topics in network measurement (see below for a non-inclusive list of topics), novel techniques are needed to cope with increasingly important subjects concerning security, privacy and forensics matters.
This area is calling for papers where a solid scientific approach is applied to real-world network measurements.
List of Topics
- Big data analytics and machine learning for network & traffic measurements analysis
- Application of Big Data frameworks (streaming, batch) to network data
- Novel or better algorithms for topology discovery, network tomography, etc.
- Measurement-driven network simulation methodologies
- Performance models from network measurements
- Network performance measurements and analysis
- Traffic & workload modeling, traffic generation techniques
- User characterization and modeling
- Quality-of-Service and Quality-of-Experience
- Application layer measurement methodologies and characterization
- Traffic classification, evasion and deanonymization
- Network anomaly detection and diagnosis
- Measurements for network security and forensics
- Measurements for privacy quantification, and privacy-preserving measurements
Area Chairs
Pedro Casas, AIT Austrian Institute of Technology, Austria
Dario Rossi, Telecom ParisTech, France
TPC Members
Urtzi Ayesta, LAAS-CNRS, France
Isabel Amigo, Telecom Bretagne, France
Sem Borst, Nokia Bell Labs, USA
Anna Brunstrom, Karlstad University, Sweden
Valentín Carela-Español, Talaia.io, Spain
Kenjiro Cho, IIJ Research Labs, Japan
Benoit Donnet, Université de Liège, Belgium
Markus Fiedler, BTH, Sweden
Luigi Iannone, Telecom ParisTech, France
Federico Larroca, Universidad de la República, Uruguay
Yingdong Lu, IBM Research, USA
John C.S. Lui, The Chinese University of Hong Kong, China
Siva Theja Maguluri, Georgia Tech, USA
Ravi Mazumdar, University of Waterloo, Canada
Luca Muscariello, Cisco System, France
Philippe Owezarski, LAAS-CNRS, France
Antonio Pescapè, University of Naples, Italy
Fabio Ricciato, University of Ljubljana, Slovenia
Anna Sperotto, University of Twente, The Netherlands
Tetsuya Takine, Osaka University, Japan
Miklos Telek, Technical University of Budapest, Hungary
Don Towsley, University of Massachusetts, USA
Roberto Gonzalez, NEC Labs, Germany
Ricardo de Oliveira Schmidt, University of Twente, The Netherlands
Georgios Smaragdakis, MIT/TU Berlin/Akamai, USA
Stefano Traverso, Politecnico di Torino, Italy
Gareth Tyson, Queen Mary University of London, UK
Guillaume Urvoy-Keller, Université Nice Sophia Antipolis, France
Benny Van Houdt, University of Antwerp, Belgium
Matteo Varvello, AT&T, USA
Rolf Winter, Augsburg University, Germany
