A Review on Comparative Analysis of Task Scheduling Algorithm for Cloud Computing Environment

Authors(2) :-Poonam Rani, Pooja Nagpal

Cloud computing is an emerging technology, that based upon internet computing and share resources (software and hardware) depends upon their demand. Cloud computing works on its important feature known as virtualization in order to access remote and geographically distributed resources. Depending upon cloud service provider and user requirements, a number of virtual machines are used. So it is necessary to schedule VM request. Most of the businesses are migrating from on-premise to the cloud and millions of users access these services daily via the internet. So it is very important to apply appropriate scheduling technique to process a large amount of data and to do resource utilization more efficiently with better performance. Nowadays scheduling task becomes a challenge for researchers. So a number of algorithms are used to provide proficiency of task and resource scheduling. . In this paper, we have discussed different scheduling algorithms like FCFS (First Come First Serve), Max-Min, Min-Min.

Authors and Affiliations

Poonam Rani
Research Scholar, Rayat Institute of Engineering & Information Technology, Ropar, Punjab, India
Pooja Nagpal
Faculty of Computer Science and Engineering, Rayat Institute of Engineering & Information Technology, Ropar, Punjab, India

Cloud Computing, scheduling, FCFS, Max-Min.

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Publication Details

Published in : Volume 3 | Issue 1 | January-February 2018
Date of Publication : 2018-02-28
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 302-307
Manuscript Number : CSEIT183142
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Poonam Rani, Pooja Nagpal, "A Review on Comparative Analysis of Task Scheduling Algorithm for Cloud Computing Environment", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 1, pp.302-307, January-February-2018.
Journal URL : http://ijsrcseit.com/CSEIT183142

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