Optimizing Map Reduce Scheduling Using Parallel Processing Model On Data Nodes in Hadoop Environment

Authors(2) :-Prof. Arjun Singh Parihar, Tarun Purohit

From the most recent years, there has been a quick progress in cloud, with the growing amounts of associations turning number of associations relying upon use resources in the cloud, there is a requirement for securing the data of various customers using concentrated resource. Circulated capacity organizations avoid the cost stockpiling organizations dodges the cost exorbitant on programming, staff keeps up and gives better execution less limit cost and flexibility, cloud advantages through web which construct their presentation to limit security vulnerabilities however security is one of the critical weaknesses that balancing incomprehensible relationship to go into appropriated processing environment. The Proposed wear down HADOOP stockpiling strategies and this purpose of interest and its impediments.

Authors and Affiliations

Prof. Arjun Singh Parihar
Sushila Devi Bansal College of Technology, Indore, Madhya Pradesh, India
Tarun Purohit
Sushila Devi Bansal College of Technology, Indore, Madhya Pradesh, India

Cloud computing, data storage, data security, HADOOP.

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Publication Details

Published in : Volume 6 | Issue 3 | May-June 2019
Date of Publication : 2019-06-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 201-206
Manuscript Number : IJSRSET1196330
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

Prof. Arjun Singh Parihar, Tarun Purohit , " Optimizing Map Reduce Scheduling Using Parallel Processing Model On Data Nodes in Hadoop Environment , International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 6, Issue 3, pp.201-206, May-June-2019.
Journal URL : http://ijsrset.com/IJSRSET1196330

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