An Energy Efficient Ant Colony System for Virtual Machine Placement in Cloud Computing

Virtual machine placement (VMP) and energy efficiency are significant topics in cloud computing research. In this paper, evolutionary computing is applied to VMP to minimize the number of active physical servers, so as to schedule underutilized servers to save energy. Inspired by the promising perfo...

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Vydáno v:IEEE transactions on evolutionary computation Ročník 22; číslo 1; s. 113 - 128
Hlavní autoři: Liu, Xiao-Fang, Zhan, Zhi-Hui, Deng, Jeremiah D., Li, Yun, Gu, Tianlong, Zhang, Jun
Médium: Journal Article
Jazyk:angličtina
Vydáno: IEEE 01.02.2018
Témata:
Algorithm design and analysis
Ant colony system (ACS)
Cloud computing
Energy consumption
Energy efficiency
Genetic algorithms
Servers
virtual machine placement (VMP)
Virtual machining
ISSN:1089-778X, 1941-0026
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Shrnutí:Virtual machine placement (VMP) and energy efficiency are significant topics in cloud computing research. In this paper, evolutionary computing is applied to VMP to minimize the number of active physical servers, so as to schedule underutilized servers to save energy. Inspired by the promising performance of the ant colony system (ACS) algorithm for combinatorial problems, an ACS-based approach is developed to achieve the VMP goal. Coupled with order exchange and migration (OEM) local search techniques, the resultant algorithm is termed an OEMACS. It effectively minimizes the number of active servers used for the assignment of virtual machines (VMs) from a global optimization perspective through a novel strategy for pheromone deposition which guides the artificial ants toward promising solutions that group candidate VMs together. The OEMACS is applied to a variety of VMP problems with differing VM sizes in cloud environments of homogenous and heterogeneous servers. The results show that the OEMACS generally outperforms conventional heuristic and other evolutionary-based approaches, especially on VMP with bottleneck resource characteristics, and offers significant savings of energy and more efficient use of different resources.
ISSN:1089-778X
1941-0026
DOI:10.1109/TEVC.2016.2623803