A virtual machine placement algorithm for balanced resource utilization in cloud data centers

2014 ◽  
Author(s):  
Nguyen Trung Hieu ◽  
Mario Di Francesco ◽  
Antti Yla-Jaaski
Keyword(s):  
Resource Utilization ◽  
Virtual Machine ◽  
Data Centers ◽  
Virtual Machine Placement ◽  
Cloud Data ◽  
Cloud Data Centers ◽  
Placement Algorithm

scholarly journals An Distributed Virtual Machine Placement Algorithm for Balanced Resource Utilization and Low Energy Consumption

2018 ◽  
Vol 173 ◽  
pp. 03092
Author(s):  
Bo Li ◽  
Yun Wang
Keyword(s):  
Virtual Machine ◽  
Data Centers ◽  
Virtual Machine Placement ◽  
Vm Placement ◽  
Energy Aware ◽  
Cloud Data ◽  
Low Energy Consumption ◽  
Cloud Data Centers ◽  
Placement Algorithm ◽  
Heterogeneous Cloud

Virtual machine placement is the process of selecting the most suitable server in large cloud data centers to deploy newly-created VMs. Traditional load balancing or energy-aware VM placement approaches either allocate VMs to PMs in centralized manner or ignore PM’s cost-capacity ratio to implement energy-aware VM placement. We address these two issues by introducing a distributed VM placement approach. A auction-based VM placement algorithm is devised for help VM to find the most suitable server in large heterogeneous cloud data centers. Our algorithm is evaluated by simulation. Experimental results show two major improvements over the existing approaches for VM placement. First, our algorithm efficiently balances the utilization of multiple types of resource by minimizing the amount of physical servers used. Second, it reduces system cost compared with existing approaches in heterogeneous environment.

Optimal virtual machine placement with multiple resources constraints in cloud data centers

2020 ◽  
Vol 39 (4) ◽  
pp. 5161-5170
Author(s):  
Zhenxiang He ◽  
Zhenjiang Li ◽  
Shengcai Zhang ◽  
Jun Lu
Keyword(s):  
Resource Utilization ◽  
Virtual Machine ◽  
Data Centers ◽  
Virtual Machine Placement ◽  
Utilization Efficiency ◽  
Ant Colony Optimization Algorithm ◽  
Cloud Data ◽  
Multiple Resources ◽  
Cloud Data Centers ◽  
Resource Utilization Efficiency

In cloud data centers, different virtual machine placement strategies will affect the resource utilization efficiency of the whole system. How to improve the overall resource utilization of the system by adjusting the virtual machine placement strategy under limited resources is the focus of current researchers. In this paper, a new virtual machine placement strategy is proposed, which is based on the comprehensive constraints of various system resources. In the process of solving the problem, a multi-objective ant colony optimization algorithm is used. Simulation results show that this method can effectively reduce the number of physical machines activated in the data center, and the accuracy is high.

scholarly journals A dynamic evolutionary multi-objective virtual machine placement heuristic for cloud data centers

2020 ◽  
Vol 128 ◽  
pp. 106390
Author(s):  
Ennio Torre ◽  
Juan J. Durillo ◽  
Vincenzo de Maio ◽  
Prateek Agrawal ◽  
Shajulin Benedict ◽  
...  
Keyword(s):  
Virtual Machine ◽  
Data Centers ◽  
Virtual Machine Placement ◽  
Cloud Data ◽  
Multi Objective ◽  
Cloud Data Centers
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