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FGENET 2014 : International Workshop on Demand Modeling and Quantitative Analysis of Future Generation Energy Networks and Energy Efficient Systems


When Mar 19, 2014 - Mar 19, 2014
Where Bamberg (Germany)
Submission Deadline Oct 27, 2013
Notification Due Dec 5, 2013
Final Version Due Dec 20, 2013
Categories    computer science   modelling   networking   measurement

Call For Papers

International Workshop on

Demand Modeling and Quantitative Analysis of Future Generation Energy Networks and Energy Efficient Systems


Call for Papers

March 19, 2014
Bamberg, Germany

General Information
Globally increasing energy demands arising from growing mobility, Internet traffic, industrial and private emissions and the steadily increasing depletion of fossil resources generate a great challenge in engineering and science.

The workshop FGENET 2014 at MMB & DFT 2014 will focus on modeling, analysis, and management of future generation energy networks, their components, attached energy-efficient systems and their monitoring, demand and planning methods. The related scientific concepts are arising from various scientific fields including economics, physics, electrical engineering and computer science. They incorporate a variety of methods.

Techniques developed by network and performance engineers in recent decades may be applied to improve the analysis and design of future smart energy networks and their attached energy-efficient systems consuming the disseminated energy flows. The focus of the workshop will be related engineering techniques arising from performance, dependability and reliability analysis. In particular the application of future smart energy networks and attached energy-efficient systems constitutes a very important, rapidly growing area in modern interconnected information societies.

The workshop will cover all aspects of modeling, analysis, and management of smart energy networks and the applied methodologies arising from the theory of performance analysis of distributed systems and dependable, fault-tolerant and highly available distributed systems. It ranges from purely theoretical achievements to practical applications regarding the structural inference, modeling, analysis, simulation, and control.

The objective is to provide a forum for researchers and practitioners to present innovative theoretical results and new research ideas that illustrate recent developments w.r.t. modeling and analysis of highly interdependent energy networks and attached systems. Fresh ideas will be exchanged and new directions will be discussed in a cross-disciplinary setting.
The workshop is co-located with the 17th International GI/ITG Conference on “Measurement, Modelling and Evaluation of Computing Systems” and “Dependability and Fault-Tolerance” (MMB & DFT 2014).

FGENET 2014 solicits novel unpublished material on modeling, analysis and control of energy networks, their management and control systems, and important energy-efficient systems attached to these networks. It includes the following topics:

Modeling, Analysis, and Simulation of Future Energy Networks including their management and control systems
quantitative analysis of network models
characterization, inference and evolution of new network topologies
robustness and vulnerability of network infrastructures
failure spreading in energy networks
dependability analysis of energy networks
fault immunization strategies
fault tolerance in energy networks
quantitative analysis of resilience strategies

Modeling and Analysis of Energy Efficiency
energy-efficient networking and protocols
energy-efficient communications management
energy-efficiency in wired networks
energy-efficiency in data centers
energy-efficiency in content delivery networks
performance modeling techniques for energy-efficient systems

Complex Network Methodologies for Energy Networks
measurement and profiling of energy consumption
wide-area monitoring
statistical methods for advanced metering infrastructure and smart metering
performance of data gathering strategies
data anonymization strategies

Measurement and Inference of Energy Consumption
characterization and inference of demand profiles
energy analytics
structural inference and analysis of the user behavior in energy networks
load and community modeling by stochastic processes
big data techniques for energy networks
tools supporting analysis, inference and prediction of consumption

Demand Modeling and Planning
emergence properties of real networks
component synchronization in energy networks
performance of signaling and distributed control protocols

Submissions and Formats
Authors are encouraged to submit a PDF version of their original contribution either as extended abstract of 4 pages or as short paper not exceeding 6 pages. All submissions must adhere to a single-column LNCS conference format with a font size not smaller than 10 points.
The paper must be submitted electronically before the deadline via Easychair at URL:

Notification of acceptance will be sent to the authors not later than December 5, 2013. In case of acceptance the final PDF version of the full paper is due by December 20, 2013.
All accepted contributions will appear in the workshop proceedings. Registration of at least one co-author as workshop or conference participant is required before the deadline.

Important Dates
Submission deadline (extended): October 25, 2013
Acceptance notification: December 5, 2013
Camera-ready version: December 20, 2013
Authors‘ registration deadline: February 15, 2014
Workshop: March 19, 2014

Organizing Committee

General Chairs
Thorsten Staake, University of Bamberg, Germany
Udo Krieger, University of Bamberg, Germany
Local Arrangement Co-Chairs
Cornelia Schecher, University of Bamberg, Germany
Marcel Großmann, University of Bamberg, Germany
Technical Program Committee
Reinhard German, University of Erlangen-Nuremberg, Germany
Hermann de Meer, University of Passau, Germany
Udo Krieger, University of Bamberg, Germany
Michael Menth, University of Tübingen, Germany
Johannes Riedl, Siemens AG Munich, Germany
Thorsten Staake, University of Bamberg, Germany

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