Energy-efficient Task Scheduling Model based on MapReduce for Cloud Computing using Genetic Algorithm
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| Title | Energy-efficient Task Scheduling Model based on MapReduce for Cloud Computing using Genetic Algorithm |
| Authors | |
| Abstract | High energy consumption of data centers hasbecome a great obstacle to the development of cloud computing.This paper mainly focuses on how to improve theenergy efficiency of servers in a data center by appropriatetask scheduling strategies. Based on MapReduce, Google’smassive data processing framework, a new energy-efficienttask scheduling model is proposed in this paper. To solvethis model, we put forward an effective genetic algorithmwith practical encoding and decoding methods and speciallydesigned genetic operators. Meanwhile, with a view toaccelerating this algorithm’s convergent speed as well asenhancing its searching ability, a local search operator isintroduced. Finally, the experiments show that the proposedalgorithm is effective and efficient. |
| Publisher | ACADEMY PUBLISHER |
| Date | 2012-12-01 |
| Source | Journal of Computers Vol 7, No 12 (2012): Special Issue: Advances in Computers and Electronics Engineering |
| Rights | Copyright © ACADEMY PUBLISHER - All Rights Reserved.To request permission, please check out URL: http://www.academypublisher.com/copyrightpermission.html. |