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Optimized Job Scheduling Approach Based on Genetic Algorithms in Smart Grid Environment.

Author(s)
Firas Albalas Department of Computer Science, Jordan University of Science and Technology, Jordan
Wail Mardini Department of Computer Science, Jordan University of Science and Technology, Jordan
Dua a Bani Ssalameh Department of Computer Science, Jordan University of Science and Technology, Jordan
Abstract
The advances in communications and information technologies have been playing a major role in all aspects of our lives. One of those majors' aspects that affect our daily lives is the power grids which lead to what we call Smart Grids. One of the major challenges in these grids is to optimize the consumption and resources. This paper presents an optimized job scheduling approach using genetic algorithm which provides a minimum cost for completing different tasks in a grid environment. In grid environment different independent appliances are sharing the same resources depending on the availability of resources and the need of these appliances to run. There are different job scheduling approached starting from typical strategies, Ant Colony (AC) and Genetic Algorithm (GA). In this paper we present a cost optimized Genetic Algorithm approach for appliances job scheduling by considering different parameters like job duration time, the resources availability and the job priority to start. The proposed approach is tested using a simulator written in c++ programming language. The results show that the total saving in cost is better than the previous approaches.
Publication Details
Page(s) 172-176
DOI DOI not available
Published Journal: International Journal of Communication Networks and Information Security, Volume: 9, Issue: 2, Year: 2017

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References
Burcea , M.,Hon,Liu,Wong , P. W. H.,Yau , D. K. Y.,Y.Xu,Zhu, 2013."Scheduling for electricity cost in smart grid,Combinatorial Optimization and Applications 8287 306 -317
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