Tasks Scheduling Method Based on Competitive Co-evolutionary Algorithm

DOI

10.2991/epee-16.2016.68How to use a DOI?

Keywords

cloud computing; co-evolution; task scheduling; workflow

Abstract

In previous studies about cloud computing scheduling algorithm, people usually ignore impact of data transmission between tasks, but data locality and data transmission have a great influence on the data-intensive task, especially for scientific workflow scheduling. This thesis explains importance of data locality and data transmission. Taking into account that users are more concerned about the completion time, a competitive co-evolutionary immune genetic algorithm, combining with immune algorithm and competitive co-evolutionary algorithm, then a new algorithm is proposed for scheduling problem in scientific workflow for data intensive tasks, which aims to minimize the completion time. Finally, In the cloud simulation platform building by CloudSim, scheduling model and corresponding algorithm proposed in this paper are carried out experiments. The results demonstrate effectiveness of the proposed scheduling algorithm.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Haijie Yu
AU  - Sheng Su
AU  - Qingguang Guo
PY  - 2016/10
DA  - 2016/10
TI  - Tasks Scheduling Method Based on Competitive Co-evolutionary Algorithm
BT  - Proceedings of the 2016 International Conference on Energy, Power and Electrical Engineering
PB  - Atlantis Press
SP  - 302
EP  - 305
SN  - 2352-5401
UR  - https://doi.org/10.2991/epee-16.2016.68
DO  - 10.2991/epee-16.2016.68
ID  - Yu2016/10
ER  -