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World Journal of Engineering
Research and Technology

( An ISO 9001:2015 Certified International Journal )

An International Peer Reviewed Journal for Engineering Research and Technology

ISSN 2454-695X

Impact Factor : 5.924

ICV : 79.45

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Indexing

Abstract

AN IMPROVED JOB SCHEDULING METHOD BY USING RELEASED RESOURCES FOR MAPREDUCE

Indumathi. S, Pavithra. T. N, Shruti. M. Masali, Thriveni. M. D*, Malatesh. S. H

ABSTRACT

Big data is defined as large amount of data which requires new technologies and architectures to make possible to extract value from it by capturing and analysis process. Big data has emerged because we are living in a society which makes increasing use of data intensive technologies. Due to such large size of data it becomes very difficult to perform effective analysis using the existing traditional techniques. Big data concept means a datasets which continue to grow so much that it becomes difficult to manage it using existing database management concepts and tools. MapReduce is a framework using which we can write applications to process huge amounts of data, in parallel, on large clusters of commodity hardware in a reliable manner. MapReduce has become one standard for big data processing. However job scheduling in this model is always a challenge for the research fraternity and several job scheduling algorithms have a already have been proposed by researchers addressing various issues. All such algorithms mostly emphasize on meeting of job deadline without taking cognizance of additional released resources being available through intermediate release of resources during processing. In this paper, we propose a new job scheduling algorithm which satisfies job deadline for all scheduled jobs along with utilization of the unused resources so that more number of jobs can be scheduled and the overall system efficiency will be increased.

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