scholarly journals Green Cloud and reduction of energy consumption

2015 ◽  
Vol 4 (1) ◽  
pp. 51-60
Author(s):  
Kamyab Khajehei
Keyword(s):  
Energy Consumption ◽  
Data Centers ◽  
Cloud Data ◽  
Active Devices ◽  
High Efficient ◽  
Efficient Data ◽  
Cloud Data Centers ◽  
Reduce Energy Consumption ◽  
Green Cloud ◽  
Reduction Of Energy Consumption

By using global application environments, cloud computing based data centers growing every day and this exponentially grows definitely effect on our environment. Researchers that have a commitment to their environment and others which was concerned about the electricity bills came up with a solution which called “Green Cloud”. Green cloud data centers based on how consume energy are known as high efficient data centers. In green cloud we try to reduce number of active devices and consume less electricity energy. In green data centers toke an advantage of VM and ability of copying, deleting and moving VMs over the data center and reduce energy consumption. This paper focused on which parts of data centers may change and how researchers found the suitable solution for each component of data centers. Also with all these problems why still the cloud data centers are the best technology for IT businesses.

scholarly journals Energy-Aware Adaptive Four Thresholds Technique for Optimal Virtual Machine Placement

2018 ◽  
Vol 8 (5) ◽  
pp. 3890
Author(s):  
A. R. Mohazabiyeh ◽  
K. H. Amirizadeh
Keyword(s):  
Energy Consumption ◽  
Virtual Machine ◽  
Data Centers ◽  
High Load ◽  
Cloud Services ◽  
Heavy Load ◽  
Cloud Data ◽  
Light Load ◽  
Cloud Data Centers ◽  
Reduce Energy Consumption

With the increasing expansion of cloud data centers and the demand for cloud services, one of the major problems facing these data centers is the “increasing growth in energy consumption ". In this paper, we propose a method to balance the burden of virtual machine resources in order to reduce energy consumption. The proposed technique is based on a four-adaptive threshold model to reduce energy consumption in physical servers and minimize SLA violation in cloud data centers. Based on the proposed technique, hosts will be grouped into five clusters: hosts with low load, hosts with a light load, hosts with a middle load, hosts with high load and finally, hosts with a heavy load. Virtual machines are transferred from the host with high load and heavy load to the hosts with light load. Also, the VMs on low hosts will be migrated to the hosts with middle load, while the host with a light load and hosts with middle load remain unchanged. The values of the thresholds are obtained on the basis of the mathematical modeling approach and the 𝐾-Means Clustering Algorithm is used for clustering of hosts. Experimental results show that applying the proposed technique will improve the load balancing and reduce the number of VM migration and reduce energy consumption.

scholarly journals Energy aware dynamic virtual machine consolidation in cloud data centers

2018 ◽  
Vol 7 (2.8) ◽  
pp. 550 ◽  
Author(s):  
G Anusha ◽  
P Supraja
Keyword(s):  
Energy Consumption ◽  
Virtual Machine ◽  
Data Centers ◽  
Energy Aware ◽  
Large Power ◽  
Complex Tasks ◽  
Cloud Data ◽  
Network Bandwidth ◽  
Virtual Machine Consolidation ◽  
Cloud Data Centers

Cloud computing is a growing technology now-a-days, which provides various resources to perform complex tasks. These complex tasks can be performed with the help of datacenters. Data centers helps the incoming tasks by providing various resources like CPU, storage, network, bandwidth and memory, which has resulted in the increase of the total number of datacenters in the world. These data centers consume large volume of energy for performing the operations and which leads to high operation costs. Resources are the key cause for the power consumption in data centers along with the air and cooling systems. Energy consumption in data centers is comparative to the resource usage. Excessive amount of energy consumption by datacenters falls out in large power bills. There is a necessity to increase the energy efficiency of such data centers. We have proposed an Energy aware dynamic virtual machine consolidation (EADVMC) model which focuses on pm selection, vm selection, vm placement phases, which results in the reduced energy consumption and the Quality of service (QoS) to a considerable level.

Optimized Renewable Energy Use in Green Cloud Data Centers

2019 ◽  
pp. 314-330
Author(s):  
Minxian Xu ◽  
Adel N. Toosi ◽  
Behrooz Bahrani ◽  
Reza Razzaghi ◽  
Martin Singh
Keyword(s):  
Renewable Energy ◽  
Energy Use ◽  
Data Centers ◽  
Cloud Data ◽  
Cloud Data Centers ◽  
Green Cloud
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