An Energy-Aware Ant Colony Algorithm for Network-Aware Virtual Machine Placement in Cloud Computing

2016 ◽  
Author(s):  
Chuangen Gao ◽  
Hua Wang ◽  
Linbo Zhai ◽  
Yanqing Gao ◽  
Shanwen Yi
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Ant Colony Algorithm ◽  
Virtual Machine Placement ◽  
Ant Colony ◽  
Energy Aware

scholarly journals Energy-Saving Virtual Machine Placement Method for User Experience in Cloud Environment

2020 ◽  
Vol 2020 ◽  
pp. 1-9 ◽  
Author(s):  
Shanchen Pang ◽  
Kexiang Xu ◽  
Shudong Wang ◽  
Min Wang ◽  
Shuyu Wang
Keyword(s):  
Energy Consumption ◽  
Energy Saving ◽  
Virtual Machine ◽  
User Experience ◽  
Ant Colony Algorithm ◽  
Data Centers ◽  
Virtual Machine Placement ◽  
Ant Colony ◽  
Local Optimum ◽  
Placement Method

Green computing focuses on the energy consumption to minimize costs and adverse environmental impacts in data centers. Improving the utilization of host computers is one of the main green cloud computing strategies to reduce energy consumption, but the high utilization of the host CPU can affect user experience, reduce the quality of service, and even lead to service-level agreement (SLA) violations. In addition, the ant colony algorithm performs well in finding suitable computing resources in unknown networks. In this paper, an energy-saving virtual machine placement method (UE-ACO) is proposed based on the improved ant colony algorithm to reduce the energy consumption and satisfy users’ experience, which achieves the balance between energy consumption and user experience in data centers. We improve the pheromone and heuristic factors of the traditional ant colony algorithm, which can guarantee that the improved algorithm can jump out of the local optimum and enter the global optimal, avoiding the premature maturity of the algorithm. Experimental results show that compared to the traditional ant colony algorithm, min-min algorithm, and round-robin algorithm, the proposed algorithm UE-ACO can save up to 20%, 24%, and 30% of energy consumption while satisfying user experience.

scholarly journals A multi-objective ant colony system algorithm for virtual machine placement in cloud computing

2013 ◽  
Vol 79 (8) ◽  
pp. 1230-1242 ◽  
Author(s):  
Yongqiang Gao ◽  
Haibing Guan ◽  
Zhengwei Qi ◽  
Yang Hou ◽  
Liang Liu
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Virtual Machine Placement ◽  
Ant Colony ◽  
Ant Colony System ◽  
Multi Objective

scholarly journals An Energy-Aware Algorithm for Virtual Machine Placement in Cloud Computing

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 55659-55668 ◽  
Author(s):  
Da-Ming Zhao ◽  
Jian-Tao Zhou ◽  
Keqin Li
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Virtual Machine Placement ◽  
Energy Aware

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

2018 ◽  
Vol 22 (1) ◽  
pp. 113-128 ◽  
Author(s):  
Xiao-Fang Liu ◽  
Zhi-Hui Zhan ◽  
Jeremiah D. Deng ◽  
Yun Li ◽  
Tianlong Gu ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Energy Efficient ◽  
Virtual Machine Placement ◽  
Ant Colony ◽  
Ant Colony System
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