scholarly journals Virtual Machine Provisioning Scheduling with Conditional Probability Inference for Transport Information Service in Cloud Environment

2011 ◽  
Vol 20 (4) ◽  
pp. 139-147 ◽  
Author(s):  
Jae-Kwon Kim ◽  
Jong-Sik Lee
Keyword(s):  
Conditional Probability ◽  
Virtual Machine ◽  
Information Service ◽  
Cloud Environment ◽  
Virtual Machine Provisioning

Augmented intelligent water drops optimisation model for virtual machine placement in cloud environment

IET Networks ◽  
2020 ◽  
Vol 9 (5) ◽  
pp. 215-222
Author(s):  
Sivaraman Eswaran ◽  
Daniel Dominic ◽  
Jayapandian Natarajan ◽  
Prasad B. Honnavalli
Keyword(s):  
Virtual Machine ◽  
Virtual Machine Placement ◽  
Cloud Environment ◽  
Water Drops ◽  
Optimisation Model ◽  
Intelligent Water Drops

scholarly journals Enhancing Energy-Efficient and QoS Dynamic Virtual Machine Consolidation Method in Cloud Environment

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 31224-31235 ◽  
Author(s):  
Yaqiu Liu ◽  
Xinyue Sun ◽  
Wei Wei ◽  
Weipeng Jing
Keyword(s):  
Virtual Machine ◽  
Energy Efficient ◽  
Cloud Environment ◽  
Virtual Machine Consolidation

scholarly journals Energy Efficient Resource Allocation in Cloud Computing

2019 ◽  
Vol 8 (6S3) ◽  
pp. 2071-2074
Keyword(s):  
Virtual Machine ◽  
Service Provider ◽  
Physical System ◽  
Virtual Machines ◽  
Cloud Service ◽  
Cloud Environment ◽  
Cloud Service Provider ◽  
Host System ◽  
Physical Systems ◽  
Single Host

Cloud service provider in cloud environment will provide or provision resource based on demand from the user. The cloud service provider (CSP) will provide resources as and when required or demanded by the user for execution of the job on the cloud environment. The CSP will perform this in a static and dynamic manner. The CSP should also consider various other factors in order to provide the resources to the user, the prime among that will be the Service Level Agreement (SLA), which is normally signed by the user and cloud service provider during the inception phase of service. There are many algorithm which are used in order to allocate resources to the user in cloud environment. The algorithm which is proposed will be used to reduce the amount of energy utilized in performing various job execution in cloud environment. Here the energy utilized for execution of various jobs are taken into account by increasing the number of virtual machines that are used on a single physical host system. There is no thumb rule to calculate the number of virtual machines to be executed on a single host. The same can be derived by calculating the amount of space, speed required along with the time to execute the job on a virtual machine. Based up on this we can derive the number of Virtual machine on a single host system. There can be 10 virtual machines on a single system or even 20 number of virtual machines on single physical system. But if the same is calculated by the equation then the result will be exactly matching with the threshold capacity of the physical system[1]. If more number of physical systems are used to execute fewer virtual machines on each then the amount of energy consumed will be very high. So in order to reduce the energy consumption , the algorithm can be used will not only will help to calculate the number of virtual machines on single physical system , but also will help to reduce the energy as less number of physical systems will be in need[2].

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