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Efficient Scheduling of Scientific Workflows with Energy Reduction Using Novel Discrete Particle Swarm Optimization and Dynamic Voltage Scaling for Computational Grids
Joint Authors
Christobel, M.
Tamil Selvi, S.
Benedict, Shajulin
Source
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-05-14
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
One of the most significant and the topmost parameters in the real world computing environment is energy.
Minimizing energy imposes benefits like reduction in power consumption, decrease in cooling rates of the computing processors, provision of a green environment, and so forth.
In fact, computation time and energy are directly proportional to each other and the minimization of computation time may yield a cost effective energy consumption.
Proficient scheduling of Bag-of-Tasks in the grid environment ravages in minimum computation time.
In this paper, a novel discrete particle swarm optimization (DPSO) algorithm based on the particle’s best position (pbDPSO) and global best position (gbDPSO) is adopted to find the global optimal solution for higher dimensions.
This novel DPSO yields better schedule with minimum computation time compared to Earliest Deadline First (EDF) and First Come First Serve (FCFS) algorithms which comparably reduces energy.
Other scheduling parameters, such as job completion ratio and lateness, are also calculated and compared with EDF and FCFS.
An energy improvement of up to 28% was obtained when Makespan Conservative Energy Reduction (MCER) and Dynamic Voltage Scaling (DVS) were used in the proposed DPSO algorithm.
American Psychological Association (APA)
Christobel, M.& Tamil Selvi, S.& Benedict, Shajulin. 2015. Efficient Scheduling of Scientific Workflows with Energy Reduction Using Novel Discrete Particle Swarm Optimization and Dynamic Voltage Scaling for Computational Grids. The Scientific World Journal،Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1079147
Modern Language Association (MLA)
Christobel, M.…[et al.]. Efficient Scheduling of Scientific Workflows with Energy Reduction Using Novel Discrete Particle Swarm Optimization and Dynamic Voltage Scaling for Computational Grids. The Scientific World Journal No. 2015 (2015), pp.1-11.
https://search.emarefa.net/detail/BIM-1079147
American Medical Association (AMA)
Christobel, M.& Tamil Selvi, S.& Benedict, Shajulin. Efficient Scheduling of Scientific Workflows with Energy Reduction Using Novel Discrete Particle Swarm Optimization and Dynamic Voltage Scaling for Computational Grids. The Scientific World Journal. 2015. Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1079147
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1079147