[hpc-announce] TNSM Special Issue on Advances in Big Data Analytics for Management (Submissions due: 3 May 2017)

Yixin Diao diao at us.ibm.com
Wed Feb 1 14:11:36 CST 2017


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IEEE Transactions on Network and Service Management

Special Issue on Advances in Big Data Analytics for Management

http://www.comsoc.org/tnsm/cfp/si-bdm

(Submissions due: 3 May 2017)

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Cloud and network analytics can harness the immense stream of
operational data from clouds and networks, and can perform analytics
processing to improve reliability, configuration, performance, and
security management. In particular, we see a growing trend towards
using statistical analysis and machine learning to improve operations
and management of IT systems and networks.

Research is therefore needed to understand and improve the potential
and suitability of Big Data analytics in the context of systems and
network management. This will not only provide deeper understanding
and better decision making based on largely collected and available
operational data, but present opportunities for improving data
analysis algorithms and methods on aspects such as accuracy and
scalability. Moreover, there is an opportunity to define novel
platforms that can harness the vast operational data and advanced data
analysis algorithms to drive management decisions in networks, data
centers, and clouds.

IEEE Transactions on Network and Service Management (IEEE TNSM) is a
premier journal for timely publication of archival research on the
management of networks, systems, services and applications. Following
the success of TNSM special issue on Big Data Analytics for Management
(September 2016), this special issue of TNSM will focus on "Advances
in Big Data Analytics for Management," presenting recent, emerging
approaches and technical solutions that can exploit Big Data and
analytics in management solutions. We welcome submissions addressing
the underlying challenges of Big Data Analytics for Management and
presenting novel theoretical or experimentation results. Survey papers
that offer a perspective on related work and identify key challenges
for future research will be considered as well.

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Topics of Interest

Topics of interest for this special issue include, but are not
limited, to the following:

Big Data Analytics and Machine Learning
- Analysis, modelling and visualization
- Operational analytics and intelligence
- Event and log analytics
- Anomaly detection and prediction
- Monitoring and measurements for management
- Harnessing social data for management
- Predictive analytics and real-time analytics
- Data mining, statistical modeling, and machine learning for management

Application Domains and Management Paradigms
- Cloud and network analytics
- Data centric management of virtualized infrastructure, clouds and data
centers
- Data centric management of storage resources and software defined
networks
- Data centric management of Internet of Things and cyber-physical systems
- Platforms for analyzing and storing logs and operational data for
management tasks
- Applications of Big data analytics to traffic classification,
root-cause analysis, service quality assurance, IT service and
resource management
- Analytics and machine learning applications to cyber-security,
intrusion detection, threat analysis, and failure detection

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Paper Submission

All papers should be submitted through the IEEE Transactions on
Network and Service Management manuscript submission site at
https://mc.manuscriptcentral.com/tnsm. Authors must indicate in the
submission cover letter that their manuscript is intended for the
"Advances in Big Data Analytics for Management" special issue. Each
submission will be limited to 14 pages in IEEE 2-column format.
Detailed author guidelines can be found at
http://www.comsoc.org/tnsm/author-guidelines.

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Important Dates

Submission Deadline: May 3, 2017
Author Notification: July 15, 2017
Revision Deadline: September 15, 2017
Final Decision: November 1, 2017
Camera Ready: December 1, 2017
Publication: March 2018

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Guest Editors

Giuliano Casale (Imperial College London, UK)
Yixin Diao (IBM T. J. Watson Research Center, USA)
Marco Mellia (Politecnico di Torino, Italy)
Rajiv Ranjan (Newcastle University, UK)
Nur Zincir-Heyood (Dalhousie University, Canada)
Albert Zomaya (University of Sydney, Australia)

For more information, please contact the guest editors at
TNSM.SI.BDM at gmail.com.
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