The First International Conference in Networking Science & Practice

Area 1: Performance evaluation, control and optimization

Short Description

Rapid advances in large-scale networked computing systems and Internet services raise a critical need for innovative analytical approaches (e.g., queueing, stochastic or other mathematical models) or data-driven models (e.g., data mining or machine learning models) for analyzing and evaluating the performance (not only in terms of speed and resource utilization but also availability and resilience) of such systems and services, both at the individual component levels and the system as a whole. Advanced optimization and control strategies are also called for to improve the overall system performance and tame the scale and complexity of networked systems and Internet applications. Game-theoretical models for understanding the interactions of many co-existing and inter-dependent systems in a competitive and yet cooperative environment are crucial as well. We solicit submissions including theoretical models and analysis as well as (empirical) data-driven analysis providing insights into the performance evaluation, optimization and control issues of real-world networked systems and Internet services.
The area also features performance modeling and analysis work that is building bridges between theory and practice, taking both innovative and established performance models to real networking scenarios and cases.

List of topics

Complex networks and network science
Network control and optimization
Theoretical advances in methodologies for studying network performance (stochastic geometry, information theory, queueing theory etc)
Application of consolidated methodologies to innovative network scenarios
Network economics and pricing
Social computing and online social networks
Mobility and traffic models
Incentive/consensus systems
Game theoretic models also in the presence of adversaries
Simulation
Performance models: matching; analysis; and interpretations
Data mining and machine learning
Blockchain analysis

Area Chairs

Bruno Tuffin, INRIA Rennes Bretagne-Atlantique, France

Bruno Tuffin is a Senior Researcher at Inria, Rennes, France. His research interests are two folds: the development Monte Carlo simulation techniques and quasi-Monte Carlo simulation techniques for the performance evaluation of telecommunication systems, and network economics analysis, including game theory.

Markus Fiedler, BTH, Sweden

Markus Fiedler is Professor of Teletraffic Systems. He is interested in teletraffic modelling and analysis, with particular interest in fluid flow models; model matching to measurements; application of performance models to real-life network scenarios; and links towards Quality of Experience.

Sem Borst, Eindhoven University of Technology, The Netherlands, and Nokia Bell Labs, USA

Sem Borst is Professor of Stochastic Operations Research at Eindhoven University of Technology and Member of Technical Staff at Nokia Bell Labs in Murray Hill. His research interests are in the area of performance evaluation models and resource allocation algorithms for large-scale stochastic systems, in particular computer-communication networks.

TPC Members

Sabine Wittevrongel, Ghent University, Belgium
Danny de Vleeschauwer, Nokia, Belgium
Samuli Aalto, Aalto University, Finland
James Roberts, IRT SystemX, France
Nancy Perrot, Orange Labs, France
Udo R. Krieger, Otto-Friedrich University Bamberg, Germany
Poul Heegard, NTNU, Norway
Rob van der Mei (Area 1 +Area 2), CWI, Netherlands
Ravi Mazumdar, University of Waterloo, Canada
Jean Walrand, Berkeley, USA
Eytan Modiano, MIT, USA
D. Manjunath, IIT Bombay, India
Costas Courcoubetis, Singapore University of Technology and Design, Singapore
John C.S. Lui, The Chinese University of Hong Kong, Hong-Kong, China
Longbo Huang, Tsinghua University, Mainland China
Yung Yi, KAIST, South Korea
Corinne Touati, INRIA, France
Benny van Houdt, University of Antwerp, Belgium
Fabrice Guillemin, Orange Labs, France
Paul J. Kühn, University of Stuttgart, Germany
Tatsuaki Kimura, NTT, Japan
Alexandra Dmitrienko, University of Würzburg, Germany