Title:	A CLOUD-BASED DATA ANALYTICAL FRAMEWORK FOR MEDIUM SCALE SCIENTIFIC APPLICATIONS
Author(s):	Reena Bharathi, Shailaja Shirwaikar, Vilas Kharat and Gajanan Aher
ISBN:	978-989-8533-66-1
Editors:	Yingcai Xiao and Ajith P. Abraham
Year:	2017
Edition:	Single
Keywords:	Cloud computing, big data analytics, Hadoop, MapReduce, Workflow
Type:	Full Paper
First Page:	213
Last Page:	222
Language:	English
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Full Contents:	click to dowload
Paper Abstract:	Data intensive science focuses on extracting, exploring and mining knowledge from a huge ever growing data that is obtained from various instruments and simulations. Scientific applications earlier were using High Performance Computers, then focus was on cluster computing and then towards grid computing. As the technologies in the networking domain improved, distributed networking and cloud computing have become prevalent. Scientific applications using cloud computing paradigm, faces several challenges such as data transportation cost, computing costs, data privacy and data security. A small dedicated cluster, with a cloud like interface, designed from low cost commodity machines, is often affordable by a group or an individual researcher, and is reasonably cost-effective. n this paper, the authors demonstrate how a low cost inexpensive cluster setup can be designed and customized as a cloud based data analytical services framework, to provide data storage and analytical capabilities, for exploratory needs of a small or medium scale scientific application.
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