Virtual Machine Scheduling to Minimize Resource Wastage in Cloud Computing Environment

DOI

10.2991/nceece-15.2016.228How to use a DOI?

Keywords

Cloud Computing; Particle Swarm Optimization; Virtual machine scheduling

Abstract

Virtual machine scheduling is the process of selecting the most suitable server in cloud data centers to deploy newly created VMs. The optimal placement is important for improving resource utilization and reducing resource wastage in a cloud computing environment. In this article, we propose an Self-Adaptive Particle Swarm Optimization for the virtual machine scheduling problem. Our algorithm focuses on efficient VM allocation to physical servers in order to minimize the total resource wastage and the number of servers used. Simulation experiments were designed to evaluate the proposed algorithm with performance and scalability. Its solution performance are compared with PSO and GPSO scheduling strategies. The results show that the proposed algorithm is more efficient and effective than the methods we compared to.

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  - Yahui Zhu
AU  - Dan Chen
PY  - 2015/12
DA  - 2015/12
TI  - Virtual Machine Scheduling to Minimize Resource Wastage in Cloud Computing Environment
BT  - Proceedings of the 2015 4th National Conference on Electrical, Electronics and Computer Engineering
PB  - Atlantis Press
SP  - 1294
EP  - 1300
SN  - 2352-5401
UR  - https://doi.org/10.2991/nceece-15.2016.228
DO  - 10.2991/nceece-15.2016.228
ID  - Zhu2015/12
ER  -