CALL FOR PAPERS
Big Data 
IEEE Transactions on Emerging Topics in Computing 

Special Issue: September 2014

 

IEEE Transactions on Emerging Topics in Computing (TETC) seeks original manuscripts for a Special Issue on Big Data scheduled to appear in the September 2014 Issue.

 

Big Data consists of datasets that grow so large that they become awkward to work with using on-hand computer data and computation management tools. Difficulties include, but are not limited to, capture, storage, search, sharing, analytics, and visualizing. Working with data sets of increasing scale allows analysts to "spot business trends, prevent diseases, and combat crime." Big data size is beyond the ability of commonly used computer software and hardware tools to capture, manage, and process the data within a tolerable elapsed time, hence demanding new innovative solutions. It has attracted a high degree of interdisciplinary interest internationally. This special issue is focusing on this new strategic research area to address challenges about big data. Original and unpublished high-quality research results are solicited to explore various challenging topics that include, but are not limited to:

 

        Big Data theoretical models, standards  and theories

        Innovative computer software and hardware architecture for Big Data processing

        Big Data mining, advanced analytics and visualization

        Large big data stream processing

        Large-scale incremental, distributed and federated datasets

        NoSQL data stores and DB scalability

        Big Data sharing and privacy preserving

        Big Data placement, scheduling, and optimization

        MapReduce and new programming models for Big Data processing

        Cloud Computing, cluster and high performance computing and storage infrastructure for Big Data

        Performance characterization, evaluation and optimization

        Simulation and debugging of Big Data systems and tools

        Security, privacy, reliability and trust in Big Data

        Volume, Velocity, Variety and Value of Big Data

        Multiple source data processing and integration for Big Data

        Resource scheduling and Service Level Agreement for Big Data processing

        Distributed file systems, storage and computation management for Big Data

        Large-scale scientific workflow in support of Big Data processing

        Big data applications such as Medicine, Healthcare, Finance, Business, Retailing, Transportation and Science.

 

Submitted articles must not have been previously published or currently submitted for journal publication elsewhere. Extended versions from conference papers such as The 2nd IEEE International Conference on Big Data Science and Engineering (BDSE2013 - http://www.swinflow.org/confs/bdds2013/ must have at least 30% new content. As an author, you are responsible for understanding and adhering to our submission guidelines. You can access them at the IEEE Computer Society web site, www.computer.org. Please thoroughly read these before submitting your manuscript. TETC is the newest Transactions of the IEEE Computer Society with Open Access only.

 

Please submit your paper to Manuscript Central at https://mc.manuscriptcentral.com/tetc-cs

 

Please note the following important dates.

        Submission Deadline: November 15, 2013 (extended)

        Reviews Completed: January 15, 2014

        Major Revisions Due (if Needed): February 15, 2014

        Reviews of Revisions Completed (if Needed): March 15, 2014

        Minor Revisions Due (if Needed): April 15, 2014

        Notification of Final Acceptance: May 15, 2014

        Publication Materials for Final Manuscripts Due: May 30, 2014

        Publication date: September 2014

 

Please address all other correspondence regarding this special issue to Coordinating Guest Editor Jinjun Chen

 

Guest Editors

Jinjun Chen, Jinjun.Chen@uts.edu.au

University of Technology Sydney, Australia

Surya Nepal, Surya.Nepal@csiro.au

CSIRO Australia

Jian Pei, jpei@cs.sfu.ca

Simon Fraser University, Canada

Ivan Stojmenovic, ivan@site.uottawa.ca

University of Ottawa, Canada