scholarly journals Role of Virtual Machine Live Migration in Cloud Load Balancing

2013 ◽  
Vol 15 (5) ◽  
pp. 69-72
Author(s):  
Stuti Dave ◽  
2014 ◽  
Vol 2014 ◽  
pp. 1-7
Author(s):  
Ming-Tsung Kao ◽  
Yu-Hsin Cheng ◽  
Shang-Juh Kao

Due to the increasing number of computer hosts deployed in an enterprise, automatic management of electronic applications is inevitable. To provide diverse services, there will be increases in procurement, maintenance, and electricity costs. Virtualization technology is getting popular in cloud computing environment, which enables the efficient use of computing resources and reduces the operating cost. In this paper, we present an automatic mechanism to consolidate virtual servers and shut down the idle physical machines during the off-peak hours, while activating more machines at peak times. Through the monitoring of system resources, heavy system loads can be evenly distributed over physical machines to achieve load balancing. By integrating the feature of load balancing with virtual machine live migration, we successfully develop an automatic private cloud management system. Experimental results demonstrate that, during the off-peak hours, we can save power consumption of about 69 W by consolidating the idle virtual servers. And the load balancing implementation has shown that two machines with 80% and 40% CPU loads can be uniformly balanced to 60% each. And, through the use of preallocated virtual machine images, the proposed mechanism can be easily applied to a large amount of physical machines.


2019 ◽  
Vol 38 (2) ◽  
pp. 291-320
Author(s):  
Petrônio Bezerra ◽  
Marcela Santos ◽  
Edlane Alves ◽  
Anderson Costa ◽  
Fellype Albuquerque ◽  
...  

2013 ◽  
Vol 66 (3) ◽  
pp. 1629-1655 ◽  
Author(s):  
Jinkyu Jeong ◽  
Sung-Hun Kim ◽  
Hwanju Kim ◽  
Joonwon Lee ◽  
Euiseong Seo

2014 ◽  
Vol 668-669 ◽  
pp. 1363-1367 ◽  
Author(s):  
Zhi Hong Sun ◽  
Xian Lang Hu

The live migration of virtual machine (VM) is an important technology of cloud computing. Down-time, total migration time and network traffic data are the key measures of performance. Through the analysis of dynamic memory state of a virtual machine migration process, we propose a dirty pages algorithm prediction based on pre-copy to avoid dirty pages re transmission. Experimental results show that, compared with the Xen virtual machine live migration method adopted, our method can at least reduce 15.1% of the total amount of data and 12.2% of the total migration time.


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