Workshop on :

Networking across disciplines: Communication Networks,

Complex Systems and Statistical Physics

(NETSTAT 2013)

http://netstat-workshop.com/

Held in conjunction with ICC 2013, Budapest, Hungary

 

(SUBMISSION DEADLINE EXTENDED to Jan.25, 2013)

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KEYNOTE SPEAKERS

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Marc Mezard, Ecole Normale Superieure

John S. Baras, University of Maryland, College Park

 

SCOPE

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Communication networks experience a culmination in their evolution, as they have evolved into multifarious architectural paradigms (such as sensory, mobile ad-hoc, wireless peer-to-peer or femto-cell based), while a myriad of heterogeneous devices create a networked environment of unprecedented complexity. Parallel to that,

social networking creates a stratum of user interaction that has a profound impact on the way information is accessed and retrieved. The increasing quest for information

in today's networked world, together with the need to efficiently access, handle

and transport the torrents of information call for real-time online decision making

and optimal control, oftentimes amidst partial state information. A more efficient

use of network resources becomes increasingly more important, due to the

substantial energy consumption by communication systems in general, and by routers

in particular, and increasing pressure on existing infrastructure. Complex behaviors

are anticipated as more entities become embedded in the massive internet

infrastructure, giving rise to non-trivial microscopic interactions which in turn

influence global system behaviors at the macroscopic level.

Statistical physics aims at understanding the collective behavior of large disordered

systems of heterogeneous, randomly interacting components that engage in localized

interactions. It provides a solid framework for studying how small-scale randomness

generates global-scale phenomena like phase transitions, which are essentially

nonrandom and are governed by system parameters and external conditions.

Recent success stories in understanding the nature of hard combinatorial problems

attest to the strong potential of insights offered by statistical physics. The

decoding process of Shannon-capacity approaching codes in digital communication and

the construction of new codes benefitted from such insights. Belief propagation

approaches that emanate from statistical physics have facilitated the landmark

achievement of reaching the information theoretic capacity in different types of noisy channels.

The NETSTAT workshop aims at bringing together individuals from a number of communities

such as communication theory, information theory, networking, and statistical physics

with the following objectives:

* Delineate a common foundational framework at the interface between these disciplines

* Harness techniques that are inspired from statistical physics principles to advance

state of the art in information communication theory and network optimization problems

* Propose methods that remove the barrier of combinatorial complexity in network control

problems by leveraging statistical physics based techniques

* Enhance statistical physics methodologies with a pragmatic view dictated by

networking problems and rigorous approaches by the information theory community.

 

TOPICS OF INTEREST

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Original contributions are solicited in areas that include (but are not limited to) the following:

* Statistical physics inspired techniques for communication network modeling and

resource allocation

* Information Communication theory and statistical physics

* Network inference problems and approaches based on statistical physics

* Non-cooperative and cooperative game models for networks

* Compressed sensing and application in networking problems

* Statistical physics inspired techniques for social networking problems

* Applications of belief propagation techniques in wireless networking, in information

theory, and in digital communication

* Phase transition phenomena in digital communications and networking

* Disordered systems, glass systems theory and other statistical physics principles,

and their applications to information theory and networking

* Network inference problems

 

IMPORTANT DATES

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* Paper submission deadline: January 25, 2013 (Extended deadline)

* Paper acceptance notification:February 22, 2013

* Camera-ready papers due: March 8, 2013

* Workshop date: June 9 or 13 (TBD), 2013

 

COMMITTEES

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Workshop Co-Chairs:

* Iordanis Koutsopoulos (University of Thessaly and CERTH, Greece)

* David Saad (Aston University, UK)

 

Technical Program Committee:

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* Dimitrios Achlioptas, National Kapodestrian University of Athens

* Tansu Alpcan - University of Melbourne

* Erik Aurell - KTH, Stockholm

* John S. Baras - University of Maryland College Park

* Misha Chertkov - Los Alamos National Lab

* Silvio Franz- Université Paris-Sud

* Leonidas Georgiadis - Aristotle University of Thessaloniki

* Paolo Giaccone - Politecnico di Torino

* Dongning Guo - Northwestern University, Chicago

* Yoshiyuki Kabashima, Tokyo Tech.

* Igor Lerner - Birmingham University

* Emilio Leonardi - Politecnico di Torino

* Enzo Marinari - Universita Roma La Sapienza

* Neri Merhav - Technion, Haifa, Israel

* Andrea Montanari – Stanford

* Aris Moustakas - National Kapodestrian University of Athens

* Ralf Müller -Norwegian Univ. of Science & Technology

* Georgios Rodolakis, CERTH

* Toshiyuki Tanaka - Kyoto University

* Leandros Tassiulas - University of Thessaly and CERTH

* Stavros Toumpis - Athens University of Economics and Business

* Rudiger Urbanke, EPFL

* Michael Wong - Hong Kong University of Science and Technology

* Igor Yurkevich - Aston University

* Riccardo Zecchina, Politecnico di Torino

* Haijun Zhou - Chinese Academy of Science, Beijing