Energy Efficient Virtual Machine Placement Approach for Balanced Resource Utilization in Cloud Environment

Author(s):  
Rajeev Kumar Gupta ◽  
◽  
R. K Pateriya ◽  
2021 ◽  
pp. 64-71
Author(s):  
Puneet Kaushal ◽  
◽  
Subash Chander ◽  
Vijay Kumar Sinha ◽  
◽  
...  

Cloud computing provides various types of services to users. The goal of virtual machine placement (VMP) is to map the best physical machine to a virtual machine. With the help of Virtual Machine Placement, we can reduce cost, maximize resource utilization, reduced energy consumption of data centers in cloud environments. The focus of Virtual Machine Placement is to saving of power, quality of service. In this paper, we have reviewed various placements techniques used in cloud computing. At last, we have also studied various challenges for virtual machine placement in cloud computing. The main motive of various types of Virtual Machine Placement algorithms have to reduced energy consumption and minimize cost by maximizing utilization of various resources in the cloud platform. For further study, the researcher should focus on these challenges for the best virtual machine placement in a cloud environment. In this paper, we critically examine the techniques, challenges, and research gaps in virtual placements in cotext with Cloud Computing. Cloud computing, placement of virtual machines becomes major problems. For finding the solution to the problem we can use the various virtual machine placement algorithms. The main motive is to reduce consumption of energy, maximum resource utilization, minimizing cost factors used for virtual to the physical machine mapping in the cloud environment. For selecting the best algorithm various optimization methods are used. With these different optimization methods, we can analyze different algorithms. There is a great scope of improvement in existing systems of virtual placements to make them more energy-efficient, more reliable, and fault-tolerant. Redundancy in cloud downloading can be made more intelligent and minimized for duplicate data while downloading and uploading.


IET Networks ◽  
2020 ◽  
Vol 9 (5) ◽  
pp. 215-222
Author(s):  
Sivaraman Eswaran ◽  
Daniel Dominic ◽  
Jayapandian Natarajan ◽  
Prasad B. Honnavalli

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