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https://hdl.handle.net/2440/117200
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Type: | Conference paper |
Title: | Efficient algorithms for VM placement in cloud data center |
Author: | Wu, J. Shen, H. |
Citation: | Communications in Computer and Information Science, 2017 / Chen, G., Shen, H., Chen, M. (ed./s), vol.729, pp.353-365 |
Publisher: | Springer |
Issue Date: | 2017 |
Series/Report no.: | Communications in Computer and Information Science; 729 |
ISBN: | 9789811064418 |
ISSN: | 1865-0929 1865-0937 |
Conference Name: | International Symposium on Parallel Architectures, Algorithms, and Programming (PAAP) (17 Jun 2017 - 18 Jun 2017 : Haikou, China) |
Editor: | Chen, G. Shen, H. Chen, M. |
Statement of Responsibility: | Jiahuai Wu and Hong Shen |
Abstract: | Virtual machine (VM) placement problem is a major issue in cloud data center. With the rapid development of cloud computing, efficient algorithms are needed to reduce the power consumption and save energy in data centers. Many models and algorithms are designed with an objective to minimize the number of physical machines (PMs) used in cloud data center. In this paper, we take into account the execution time of the PM, and formulate a new optimization problem of VM placement, which aims to minimize the total execution time of the PMs. We discuss the NP-hardness of the problem, and present heuristic algorithms to solve it under both offline and online scenario. Furthermore, we conduct experiments to evaluate the performance of the proposed algorithms and the result show that our methods are able to perform better than other commonly used algorithms. |
Keywords: | Cloud data center virtual machine placement bin packing Heuristic algorithm |
Rights: | © Springer Nature Singapore Pte Ltd. 2017 |
DOI: | 10.1007/978-981-10-6442-5_32 |
Grant ID: | http://purl.org/au-research/grants/arc/DP150104871 |
Published version: | http://dx.doi.org/10.1007/978-981-10-6442-5_32 |
Appears in Collections: | Aurora harvest 3 Computer Science publications |
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