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Overview of Big Data-Intensive Storage and its Technologies for Cloud and Fog Computing
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Author(s): Richard S. Segall (Arkansas State University, Jonesboro, USA), Jeffrey S. Cook (Independent Researcher, Paragould, USA)and Gao Niu (Bryant University, Smithfield, USA)
Copyright: 2019
Volume: 2
Issue: 1
Pages: 40
Source title:
International Journal of Fog Computing (IJFC)
Editor(s)-in-Chief: Sam Goundar (Victoria University of Wellington, New Zealand)and Kashif Munir (National College of Business Administration & Economics, Pakistan)
DOI: 10.4018/IJFC.2019010104
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Abstract
Computing systems are becoming increasingly data-intensive because of the explosion of data and the needs for processing the data, and subsequently storage management is critical to application performance in such data-intensive computing systems. However, if existing resource management frameworks in these systems lack the support for storage management, this would cause unpredictable performance degradation when applications are under input/output (I/O) contention. Storage management of data-intensive systems is a challenge. Big Data plays a most major role in storage systems for data-intensive computing. This article deals with these difficulties along with discussion of High Performance Computing (HPC) systems, background for storage systems for data-intensive applications, storage patterns and storage mechanisms for Big Data, the Top 10 Cloud Storage Systems for data-intensive computing in today's world, and the interface between Big Data Intensive Storage and Cloud/Fog Computing. Big Data storage and its server statistics and usage distributions for the Top 500 Supercomputers in the world are also presented graphically and discussed as data-intensive storage components that can be interfaced with Fog-to-cloud interactions and enabling protocols.
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