2012-02-02: CFP: IEEE Network, Special Issue on Computer Network Visualization: Difference between revisions

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(New page: == Call for Papers == '''[http://dl.comsoc.org/livepubs/ni/ IEEE Network Magazine]''' '''Special Issue on Computer Network Visualization, Nov./Dec. 2012 issue''' === Background === Co...)
 
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==== Guest Editors ====
==== Guest Editors ====


John Goodall, Oak Ridge National Lab, [[jgoodall@ornl.gov]]
John Goodall, Oak Ridge National Lab, [mailto:jgoodall@ornl.gov jgoodall@ornl.gov]


John Gerth, Stanford University, [[gerth@graphics.stanford.edu]]
John Gerth, Stanford University, [mailto:gerth@graphics.stanford.edu gerth@graphics.stanford.edu]


Florian Mansmann, University of Konstanz, [[Florian.Mansmann@uni-konstanz.de]]
Florian Mansmann, University of Konstanz, [mailto:Florian.Mansmann@uni-konstanz.de Florian.Mansmann@uni-konstanz.de]





Revision as of 16:30, 3 February 2012

Call for Papers

IEEE Network Magazine

Special Issue on Computer Network Visualization, Nov./Dec. 2012 issue

Background

Computer networks are dynamic, growing, and continually evolving. As complexity grows, it becomes harder to effectively communicate to human decision-makers the results of methods and metrics for monitoring networks, classifying traffic, and identifying malicious or abnormal events. Network administrators and security analysts require tools that help them understand, reason about, and make decisions about the information their analytic systems produce. To this end, information visualization and visual analytics hold great promise for making the information accessible, usable, and actionable by taking advantage of the human perceptual abilities. Information visualization techniques help network administrators and security analysts to quickly recognize patterns and anomalies; visually integrate heterogeneous data sources; and provide context for critical events.

Scope

This special issue seeks original articles examining the state of the art, open issues, research results, evaluations of visualization and visual analytic tools, and future research directions in computer network visualization and visual analytics. All submissions should be written to be understandable and appealing to a general audience. Research papers should contain a substantial amount of tutorial content and minimal mathematics. Topics of interest include, but are not limited to:

  • Uses of visualization for network status monitoring and situational awareness
  • Visualization methods employed in the classification of network traffic and its analysis
  • Visualization methods enhancing network intrusion detection and anomaly detection
  • Visualization methods for the analysis of network threats (e.g. botnets)
  • Visualization methods for the analysis of network routing
  • Methods for integrating analytics and visualization together for network analysis tasks
  • Methods for visually integrating heterogeneous data sources to support network analysis tasks
  • Case studies of open source visualization tools in network analysis tasks
  • Evaluations of network visualization tools in situ

Manuscript Submission

Articles should be written in a style comprehensible and appealing to readers outside the speciality of the article. Authors must follow the IEEE Network Magazine guidelines regarding the manuscript and its format. For details, please refer to the "Guidelines for manuscripts" at the IEEE Network Magazine web site at http://dl.comsoc.org/livepubs/ni/info/authors.html. Submitted papers must be original work and must not be under consideration for publication in other venues. Authors should submit their manuscripts in PDF through ScholarOne for IEEE Network Magazine. Choose this special issue from the drop down menu on the submission page. Authors uncertain about the relevance of their paper to this special issue should inquire with the guest editors before submission.

Schedule

Submissions: April 1, 2012

Author notifications: July 1, 2012

Final papers: September 1, 2012

Publication: November 2012

Guest Editors

John Goodall, Oak Ridge National Lab, jgoodall@ornl.gov

John Gerth, Stanford University, gerth@graphics.stanford.edu

Florian Mansmann, University of Konstanz, Florian.Mansmann@uni-konstanz.de