Applying Reinforcement Learning towards automating energy efficient virtual machine consolidation in cloud data centers

2021 ◽  
pp. 101722
Author(s):  
Rachael Shaw ◽  
Enda Howley ◽  
Enda Barrett
Keyword(s):  
Reinforcement Learning ◽  
Virtual Machine ◽  
Energy Efficient ◽  
Data Centers ◽  
Cloud Data ◽  
Virtual Machine Consolidation ◽  
Cloud Data Centers

Energy-efficient framework for virtual machine consolidation in cloud data centers

2017 ◽  
Vol 14 (10) ◽  
pp. 192-201 ◽  
Author(s):  
Kejing He ◽  
Zhibo Li ◽  
Dongyan Deng ◽  
Yanhua Chen
Keyword(s):  
Virtual Machine ◽  
Energy Efficient ◽  
Data Centers ◽  
Cloud Data ◽  
Virtual Machine Consolidation ◽  
Cloud Data Centers

scholarly journals Energy-Efficient Algorithms for Dynamic Virtual Machine Consolidation in Cloud Data Centers

IEEE Access ◽  
2017 ◽  
Vol 5 ◽  
pp. 10709-10722 ◽  
Author(s):  
Mohammad Ali Khoshkholghi ◽  
Mohd Noor Derahman ◽  
Azizol Abdullah ◽  
Shamala Subramaniam ◽  
Mohamed Othman
Keyword(s):  
Virtual Machine ◽  
Energy Efficient ◽  
Data Centers ◽  
Efficient Algorithms ◽  
Cloud Data ◽  
Virtual Machine Consolidation ◽  
Cloud Data Centers

Energy-efficient virtual machine consolidation algorithm in cloud data centers

2017 ◽  
Vol 24 (10) ◽  
pp. 2331-2341 ◽  
Author(s):  
Zhou Zhou ◽  
Zhi-gang Hu ◽  
Jun-yang Yu ◽  
Jemal Abawajy ◽  
Morshed Chowdhury
Keyword(s):  
Virtual Machine ◽  
Energy Efficient ◽  
Data Centers ◽  
Cloud Data ◽  
Virtual Machine Consolidation ◽  
Cloud Data Centers

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.

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