Research and Simulation of Task Scheduling Strategy in Cloud Computing

DOI

10.2991/msota-16.2016.4How to use a DOI?

Keywords

component; cloud computing; task scheduling; differential evolution algorithm; weighted round-robinalgorithm

Abstract

How to make full use of resources in the cloud to efficiently schedule tasks is an important issue in the field of cloud computing. This paper proposes a cloud computing task scheduling algorithm based on optimized Differential Evolution Algorithm(DE), which introduces the initial population model based on the Weighted Round-Robin Scheduling Algorithm, and makes the two control parameters of the algorithm adaptively adjust with the iteration number increase. When the task scheduling model is established, considering the user needs and the interests of the cloud provider, the execution time, the execution cost, the resource utilization rate and the execution energy consumption are taken as the scheduling targets. The optimal differential evolution algorithm is used to solve the task model, and an optimal scheduling scheme is obtained. The simulation results show that the improved algorithm can improve the scheduling performance and the effect is better

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  - Tao Lin
AU  - Qianqian Xuan
AU  - Qingguo Xu
AU  - Mengxian Wu
PY  - 2016/12
DA  - 2016/12
TI  - Research and Simulation of Task Scheduling Strategy in Cloud Computing
BT  - Proceedings of 2016 International Conference on Modeling, Simulation and Optimization Technologies and Applications (MSOTA2016)
PB  - Atlantis Press
SP  - 13
EP  - 18
SN  - 2352-538X
UR  - https://doi.org/10.2991/msota-16.2016.4
DO  - 10.2991/msota-16.2016.4
ID  - Lin2016/12
ER  -