Diversification of Cloud Resource Allocation based on Improved Genetic Algorithm

DOI

10.2991/wartia-16.2016.369How to use a DOI?

Keywords

cloud resource allocation, Service-based Software system, genetic algorithm.

Abstract

Considering the optimization and multiple service levels agreement, this paper converts the resource allocation problem of Service-Based Software system in the cloud environment into a multi-objective optimization problem. Aiming at the cloud service resource allocation problem, this paper establishes a cloud resource optimization allocation model, and proposes a diversity elastic resource allocation algorithm based on genetic algorithm to solve the problem. To improve the efficiency, Algorithm uses integer coding, and in the selection operator, the elite reservation strategy and tournament strategy are introduced to ensure the convergence to the global optimal solution. In order to improve the global searching ability of genetic algorithm and to speed up the convergence rate, this paper adopts the adaptive mutation operator. Experiments verify the proposed resource optimization assignment model and solution algorithm effective, and show that the improved genetic algorithm can rapidly acquire with lower cost and higher resource utilization efficiency of the resources allocation strategy in large scale.

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  - Jian Wang
AU  - WenYang Ke
AU  - Ying Yin
AU  - Bin Zhang
PY  - 2016/05
DA  - 2016/05
TI  - Diversification of Cloud Resource Allocation based on Improved Genetic Algorithm
BT  - Proceedings of the 2016 2nd Workshop on Advanced Research and Technology in Industry Applications
PB  - Atlantis Press
SP  - 1860
EP  - 1864
SN  - 2352-5401
UR  - https://doi.org/10.2991/wartia-16.2016.369
DO  - 10.2991/wartia-16.2016.369
ID  - Wang2016/05
ER  -