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Data Intensive Cloud Computing: Issues and Challenges

Data Intensive Cloud Computing: Issues and Challenges
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Author(s): Jayalakshmi D. S. (M. S. Ramaiah Institute of Technology, India), R. Srinivasan (S. R. M. University, India)and K. G. Srinivasa (M. S. Ramaiah Institute of Technology, India)
Copyright: 2016
Pages: 16
Source title: Big Data: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-4666-9840-6.ch029

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Abstract

Processing Big Data is a huge challenge for today's technology. There is a need to find, apply and analyze new ways of computing to make use of the Big Data so as to derive business and scientific value from it. Cloud computing with its promise of seemingly infinite computing resources is seen as the solution to this problem. Data Intensive computing on cloud builds upon the already mature parallel and distributed computing technologies such HPC, grid and cluster computing. However, handling Big Data in the cloud presents its own challenges. In this chapter, we analyze issues specific to data intensive cloud computing and provides a study on available solutions in programming models, data distribution and replication, resource provisioning and scheduling with reference to data intensive applications in cloud. Future directions for further research enabling data intensive cloud applications in cloud environment are identified.

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