Cloud Computing Resource Scheduling Research Based on the Improved Quantum Genetic Algorithm

DOI

10.2991/jiaet-18.2018.67How to use a DOI?

Keywords

Cloud computing; K value clustering; Genetic algorithm

Abstract

By aiming at the situation of applying the existing intelligent algorithm to the cloud computing job scheduling and giving analysis and comparison, it proposes the method combining K value clustering with genetic algorithm. The improved genetic algorithm with the solved individual fitness in genetic algorithm corresponding to the resource sequence in cloud computing and obtained after dynamic adjustment of rotation angle and quantum mutation and crossover has global searching ability, and can then avoid disadvantages of the existing algorithm effectively and realize optimized solution of the problems finally.

Copyright

© 2018, 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/).

Download article (PDF)

TY  - CONF
AU  - Lijun Mao
AU  - Xinyan Wang
AU  - Jing Li
PY  - 2018/03
DA  - 2018/03
TI  - Cloud Computing Resource Scheduling Research Based on the Improved Quantum Genetic Algorithm
BT  - Proceedings of the 2018 Joint International Advanced Engineering and Technology Research Conference (JIAET 2018)
PB  - Atlantis Press
SP  - 376
EP  - 381
SN  - 2352-5401
UR  - https://doi.org/10.2991/jiaet-18.2018.67
DO  - 10.2991/jiaet-18.2018.67
ID  - Mao2018/03
ER  -