Network Congestion Awareness in Cloud Data Center with Virtual Machine Migration

2020 ◽  
Author(s):  
Jiankang Dong
Keyword(s):  
Virtual Machine ◽  
Data Center ◽  
Network Congestion ◽  
Virtual Machine Migration ◽  
Cloud Data Center ◽  
Cloud Data ◽  
Congestion Awareness

scholarly journals FHCS: Hybridised optimisation for virtual machine migration and task scheduling in cloud data center

2020 ◽  
Vol 14 (12) ◽  
pp. 1942-1948
Author(s):  
Banavath Balaji Naik ◽  
Dhananjay Singh ◽  
Arun B. Samaddar
Keyword(s):  
Virtual Machine ◽  
Task Scheduling ◽  
Data Center ◽  
Virtual Machine Migration ◽  
Cloud Data Center ◽  
Cloud Data ◽  
And Task

scholarly journals A Mobility-Oriented Scheme for Virtual Machine Migration in Cloud Data Center Network

IEEE Access ◽  
2016 ◽  
Vol 4 ◽  
pp. 8327-8337 ◽  
Author(s):  
Bo Hu ◽  
Shanzhi Chen ◽  
Jianye Chen ◽  
Zhangfeng Hu
Keyword(s):  
Virtual Machine ◽  
Data Center ◽  
Data Center Network ◽  
Virtual Machine Migration ◽  
Cloud Data Center ◽  
Cloud Data

Virtual Machine Migrating Algorithm Based on Genetic Algorithm in Cloud Data Center

2014 ◽  
Vol 513-517 ◽  
pp. 2031-2034
Author(s):  
Hui Zhang ◽  
Yong Liu
Keyword(s):  
Genetic Algorithm ◽  
Resource Utilization ◽  
Virtual Machine ◽  
Data Center ◽  
Virtual Machines ◽  
Heuristic Algorithms ◽  
Optimal Solution ◽  
Virtual Machine Migration ◽  
Cloud Data Center ◽  
Cloud Data

Virtual machine migration is an effective method to improve the resource utilization of cloud data center. The common migration methods use heuristic algorithms to allocation virtual machines, the solution results is easy to fall into local optimal solution. Therefore, an algorithm called Migrating algorithm based on Genetic Algorithm (MGA) is introduced in this paper, which roots from genetic evolution theory to achieve global optimal search in the map of virtual machines to target nodes, and improves the objective function of Genetic Algorithm by setting the resource utilization of virtual machine and target node as an input factor into the calculation process. There is a contrast between MGA, Single Threshold (ST) and Double Threshold (DT) through simulation experiments, the results show that the MGA can effectively reduce migrations times and the number of host machine used.

Support vector machine approach for virtual machine migration in cloud data center

2014 ◽  
Vol 74 (10) ◽  
pp. 3419-3440 ◽  
Author(s):  
Fan-Hsun Tseng ◽  
Xiaojiao Chen ◽  
Li-Der Chou ◽  
Han-Chieh Chao ◽  
Shiping Chen
Keyword(s):  
Support Vector Machine ◽  
Virtual Machine ◽  
Data Center ◽  
Support Vector ◽  
Virtual Machine Migration ◽  
Cloud Data Center ◽  
Cloud Data
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