An Adaptive Traffic-Aware Migration Algorithm Selection Framework in Live Migration of Multiple Virtual Machines

2020 ◽  
Vol 16 (2) ◽  
pp. 314
Author(s):  
Cui Yong ◽  
Zhu Liang ◽  
Cai Zengyu ◽  
Hu Ying
Keyword(s):  
Virtual Machines ◽  
Live Migration ◽  
Algorithm Selection ◽  
Selection Framework

Adaptive Downtime for Live Migration of Virtual Machines

2014 ◽  
Author(s):  
Francisco J. Clemente-Castello ◽  
Juan Carlos Fernandez ◽  
Rafael Mayo ◽  
Enrique S. Quintana-Orti
Keyword(s):  
Virtual Machines ◽  
Live Migration

scholarly journals Live Migration of Virtual Machines Using a Mamdani Fuzzy Inference System

2022 ◽  
Vol 71 (2) ◽  
pp. 3019-3033
Author(s):  
Tahir Alyas ◽  
Iqra Javed ◽  
Abdallah Namoun ◽  
Ali Tufail ◽  
Sami Alshmrany ◽  
...  
Keyword(s):  
Fuzzy Inference System ◽  
Virtual Machines ◽  
Fuzzy Inference ◽  
Live Migration ◽  
Inference System ◽  
Mamdani Fuzzy Inference System

scholarly journals Performance degradation assessment and VM placement policy in cloud

2019 ◽  
Vol 9 (6) ◽  
pp. 4961
Author(s):  
Susmita J. A. Nair ◽  
T. R. Gopalakrishnan Nair
Keyword(s):  
Performance Assessment ◽  
Virtual Machines ◽  
Live Migration ◽  
Migration Process ◽  
Vm Migration ◽  
Physical Machine ◽  
Novel Approach ◽  
Migration Strategies ◽  
Performance Variations ◽  
Migration Technique

In virtualized servers, with live migration technique pages are copied from one physical machine to another while the virtual machine (VM) is running. The dynamic migration of virtual machines encumbers the data center which in turn reduces the performance of applications running on that particular physical machine. A considerable number of studies have been carried out in the area of performance evaluation during live VM migration.  However, all the aspects related to the migration process have not been examined for the performance assessment. In this paper, we propose a novel approach to evaluate the performance during migration process in different types of coupled machine environment. It is presented here that the state of art VM migration technology requires further improvement in realizing effective migration by monitoring comprehensive performance value. We introduced the parameter, θ, to compare performance value which can be used for controlling and halting unsuccessful migration and save significant amount of time in migration operation.  Our model is capable of analyzing real time scenario of cloud performance assessment targeting VM migration strategies. It also offers the possibility of further expanding to universal models for analyzing the performance variations that occurs as a result of VM migration.

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