Task Scheduling Algorithm based on Resources Segregation in Cloud Environment

Authors(2) :-Prof. Shailendra Raghuvanshi, Priyanka Dubey

Load balancing of non-preemptive independent tasks on virtual machines (VMs) is an important aspect of task scheduling in clouds. Whenever certain VMs are overloaded and remaining VMs are under loaded with tasks for processing, the load has to be balanced to achieve optimal machine utilization. In this paper, we propose an algorithm named honey bee behavior inspired load balancing, which aims to achieve well balanced load across virtual machines for maximizing the throughput. The proposed algorithm also balances the priorities of tasks on the machines in such a way that the amount of waiting time of the tasks in the queue is minimal. We have compared the proposed algorithm with existing load balancing and scheduling algorithms. The experimental results show that the algorithm is effective when compared with existing algorithms. Our approach illustrates that there is a significant improvement in average execution time and reduction in waiting time of tasks on queue using workflowsim simulator in JAVA.

Authors and Affiliations

Prof. Shailendra Raghuvanshi
Takshila Institute of Engineering and Technology, Jabalpur, Madhya Pradesh, India
Priyanka Dubey
Takshila Institute of Engineering and Technology, Jabalpur, Madhya Pradesh, India

Workflowssim Simulator, Java, Enhanced Max-Min, Load; Convergent Coherence

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Publication Details

Published in : Volume 4 | Issue 11 | November-December 2018
Date of Publication : 2018-12-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 96-101
Manuscript Number : IJSRSET21841125
Publisher : Technoscience Academy

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

Cite This Article :

Prof. Shailendra Raghuvanshi, Priyanka Dubey, " Task Scheduling Algorithm based on Resources Segregation in Cloud Environment, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 4, Issue 11, pp.96-101, November-December-2018. Available at doi : https://doi.org/10.32628/IJSRSET21841125
Journal URL : http://ijsrset.com/IJSRSET21841125

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