Research on Cloud Task Scheduling based on Multi-Objective Optimization

DOI

10.2991/mecae-17.2017.89How to use a DOI?

Keywords

Cloud computing, Task scheduling, Multi-objective optimization, Memetic algorithm.

Abstract

The efficient task scheduling in cloud environment has become the main research topic recently, the execution time, execution cost and load balancing for optimization in a cloud environment is significant. The scheduling of execution time and cost is a NP-hard multi-objective optimization problem, however, the current task scheduling under the cloud environment is generally the execution time or cost of single objective optimization with constraint conditions, incompletely meeting the complex cloud systems with load balancing. Given above motivations, in this paper, we propose a Memetic algorithm (MA, Memetic Algorithm) aiming at cloud task scheduling. Standardizing the objective function, the algorithm introduces the selection scheme based on the roulette, and Hill Climbing algorithm as local search. At last, we demonstrate the feasibility and efficiency of the proposed approach on the CloudSim simulator.

Copyright

© 2017, 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  - Xiaohong Hao
AU  - Yufang Han
AU  - Juan Cao
AU  - Yan Yan
AU  - Dongjiang Wang
PY  - 2017/03
DA  - 2017/03
TI  - Research on Cloud Task Scheduling based on Multi-Objective Optimization
BT  - Proceedings of the 2017 International Conference on Mechanical, Electronic, Control and Automation Engineering (MECAE 2017)
PB  - Atlantis Press
SP  - 466
EP  - 471
SN  - 2352-5401
UR  - https://doi.org/10.2991/mecae-17.2017.89
DO  - 10.2991/mecae-17.2017.89
ID  - Hao2017/03
ER  -