In the era of big data, developing modern computing systems and system software that can scale to massive amounts of data becomes a key challenge to both researchers and practitioners. Scalability in distributed system usually means that the performance of a system should increase proportionally with the increase of resources. However, this is not sufficient in the big data era. The system should be designed in a way so that all the five Vs of big data can be tackled.
Driven by this insight, this special issue aims at presenting the current state-of-the-art research and future trends on various aspects of big data programming and system software techniques for big data processing. We look for papers discussing how to build highly adaptive big data systems that can automatically adapt their behaviors to the amount of available resources, including methodologies, modeling, analysis, and newly introduced applications. Besides the latest research achievements, this special issue also covers innovative commercial data management systems, innovative commercial applications of big data technology, and experience in applying recent research advances to real-world problems. The papers will be peer reviewed and selected on the basis of both their quality and their relevance to the theme of this special issue.
Potential topics include, but are not limited to:
Authors can submit their manuscripts via the Manuscript Tracking System athttp://mts.hindawi.com/submit/journals/sp/abdp/.
| Manuscript Due | Friday, 4 November 2016 |
| First Round of Reviews | Friday, 27 January 2017 |
| Publication Date | Friday, 24 March 2017 |
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Posted 30-08-2016 on 08:29:30 AEDT