An Enhanced Optimization Technique for Scheduling In Cloud Based Applications

Authors(2) :-S. Saranya Devi, G. Muthulakshmi

Cloud offers more services which is a good choice for high resource demanding. In the complex and oversized network, the utilization of the available computation resources like processor, storage, data and services and so on around the world in commercialized manner is possible with the help of cloud computing. But the scarcity of resources requires the effective scheduling algorithm to schedule the task in effective manner by reducing cost of execution and achieve resource utilization effectively. Many scheduling mechanisms have been developed by researchers such as Cost and Energy Aware Scheduling, Cloud Based Workflow Scheduling, Multi Objective Scheduling Method Based on Ant Colony Optimization, etc. Fuzzy based optimization has proposed which makes the scheduling decision by evaluating entire group of task in job queue manner. The simulation result shows cost of execution and resource utilization are independent of each other which are executed separately by different algorithm.

Authors and Affiliations

S. Saranya Devi
PG Scholar, Department of CSE, Anna University Regional Campus Coimbatore, Tamilnadu, India
G. Muthulakshmi
Department of CSE, Anna University Regional Campus Coimbatore, Tamilnadu, India

Cloud Computing, Scheduling Algorithms, Resource Utilization, Cost of Execution, jfuzzy

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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) : 918-920
Manuscript Number : CSEIT1831125
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

S. Saranya Devi, G. Muthulakshmi, "An Enhanced Optimization Technique for Scheduling In Cloud Based Applications", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 1, pp.918-920, January-February-2018.
Journal URL : http://ijsrcseit.com/CSEIT1831125

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