scholarly journals Energy-Efficient Many-Objective Virtual Machine Placement Optimization in a Cloud Computing Environment

IEEE Access ◽  
2017 ◽  
Vol 5 ◽  
pp. 16006-16020 ◽  
Author(s):  
Xin Ye ◽  
Yanli Yin ◽  
Lan Lan
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Energy Efficient ◽  
Virtual Machine Placement ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
Placement Optimization

Virtual Machine Placement Using Statistical Mechanism in Cloud Computing Environment

2018 ◽  
Vol 9 (3) ◽  
pp. 23-31
Author(s):  
Narander Kumar ◽  
Surendra Kumar
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Virtual Machine ◽  
Minimum Cost ◽  
Virtual Machine Placement ◽  
The Internet ◽  
Computing Environment ◽  
Assignment Problems ◽  
Cloud Computing Environment ◽  
Statistical Mechanism

The internet has become essential and is the basis of cloud computing and will continue to be in the future. Best resource allocation is a process of placing the resources at their minimum cost/time and minimizes the load to a virtual machine. In this article, the authors propose an algorithm to optimize assignment problems and get the best placements in the resources to maintain the load on the virtual machine. Further, they also make comparisons between various optimization mechanisms for assignment problems, which is formulated for the cloud in virtual machine placement.

scholarly journals A Hybrid Technique for Server Consolidation in Cloud Computing Environment

2020 ◽  
Vol 20 (1) ◽  
pp. 36-52
Author(s):  
C. Vijaya ◽  
P. Srinivasan
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Virtual Machines ◽  
Virtual Machine Placement ◽  
Hybrid Technique ◽  
Computing Environment ◽  
Placement Problem ◽  
Cloud Computing Environment ◽  
Server Consolidation ◽  
Memory Utilization

AbstractThe goal of data centers in the cloud computing environment is to provision the workloads and the computing resources as demanded by the users without the intervention of the providers. To achieve this, virtualization based server consolidation acts as a vital part in virtual machine placement process. Consolidating the Virtual Machines (VMs) on the Physical Machines (PMs) cuts down the unused physical servers, decreasing the energy consumption, while keeping the constraints for CPU and memory utilization. This technique also reduces the resource wastage and optimizes the available resources efficiently. Ant Colony Optimization (ACO) that is a well-known multi objective heuristic algorithm and Grey Wolf Algorithm (GWO) has been used to consolidate the servers used in the virtual machine placement problem. The proposed Fuzzy HAGA algorithm outperforms the other algorithms MMAS, ACS, FFD and Fuzzy ACS compared against it as the number of processors and memory utilization are lesser than these algorithms.

Sign in / Sign up

Export Citation Format

Share Document