Description

AI and Machine Learning are currently being exploited in almost every scientific fields. However, networking has still a limited development and deployment of these techniques.

AI can be effectively used in many networking areas, such as fault isolation, intrusion detection, event correlation, log analysis, capacity planning, and design optimization, just to name a few.  Moreover, the complexity of today networks makes it challenging to design scalable network measurement and analysis techniques and tools. Machine learning and big data analytics techniques promise to shed light on this enormous amount of data, but smart and scalable approaches must be conceived to make them applicable to the networking practice.

WAIN workshop aims at showing to the community new contributions in this field. It looks for smart approaches and uses cases useful for understanding when and how applying AI in networking.  The workshop will allow researchers and practitioners to share their experiences and ideas and discuss the open issues related to the application of machine learning to computer networks data.

Call for paper

Important Dates

Draft paper submission deadline:2018-09-12

Topics of submission

The following is a non-exhaustive list of topics of interest for WAIN workshop:

  • Applications of ML in communication networks
  • Data analytics and mining  in networking
  • Traffic monitoring through AI
  • Application of deep learning and reinforced-learning in networking
  • Benchmarks design for big data or ML
  • Protocol design using ML
  • Methodologies for network anomaly detection and cybersecurity
  • Visualization for network characteristics and traffic monitoring
  • Requirements and expectations when using AI
  • AI applied to IoT, 5G or cloud
  • Performance Optimization through ML and Big Data
  • Experiences and best-practices using machine learning in operational networks
  • Reproducibility of ML in networking

Committee

Program Committee

  • Marco Canini, KAUST (Saudi Arabia)

  • Edmundo de Souza e Silva, Federal University of Rio de Janeiro (Brazil)

  • Lixin Gao, UMASS (USA)

  • Danilo Giordano, Politecnico di Torino (Italy)

  • Leana Golubchik, University of Southern California (USA)

  • Dan Li, Tsinghua University (China)

  • Marco Mellia, Politecnico di Torino (Italy)

  • Giovanni Neglia, Inria (France)

  • Daniel Sadoc Menasche, Federal University of Rio de Janeiro (Brazil)

  • Rayadurgam Srikant, UIUC (USA)

  • Patrick Thiran, EPFL (Switzerland)

  • Martino Trevisan, Politecnico di Torino (Italy)

  • Hui Zang, Huawei Research (USA)

  • Nur Zincir-Heywood, Dalhousie University (Canada)

  • Song Chong, KAIST, (South Korea)

Organizing committee

  • Luca Vassio, Politecnico di Torino (Italy)

  • Zhi-Li Zhang, University of Minnesota (USA)

  • Sung-Ju Lee, KAIST (Korea)

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Contact information

  • luca.vassio@polito.it