Energy-Aware on-chip virtual machine placement for cloud-supported cyber-physical systems

2017 ◽  
Vol 52 ◽  
pp. 427-437 ◽  
Author(s):  
Xuanzhang Liu ◽  
Huaxi Gu ◽  
Haibo Zhang ◽  
Feiyang Liu ◽  
Yawen Chen ◽  
...  
2018 ◽  
Vol 173 ◽  
pp. 03092
Author(s):  
Bo Li ◽  
Yun Wang

Virtual machine placement is the process of selecting the most suitable server in large cloud data centers to deploy newly-created VMs. Traditional load balancing or energy-aware VM placement approaches either allocate VMs to PMs in centralized manner or ignore PM’s cost-capacity ratio to implement energy-aware VM placement. We address these two issues by introducing a distributed VM placement approach. A auction-based VM placement algorithm is devised for help VM to find the most suitable server in large heterogeneous cloud data centers. Our algorithm is evaluated by simulation. Experimental results show two major improvements over the existing approaches for VM placement. First, our algorithm efficiently balances the utilization of multiple types of resource by minimizing the amount of physical servers used. Second, it reduces system cost compared with existing approaches in heterogeneous environment.


2019 ◽  
Vol 91 ◽  
pp. 536-554 ◽  
Author(s):  
Daniel-Jesus Munoz ◽  
José A. Montenegro ◽  
Mónica Pinto ◽  
Lidia Fuentes

2021 ◽  
Author(s):  
Reza Soltani ◽  
Eun-Young Kang ◽  
Juan Esteban Heredia Mena

2017 ◽  
Vol 9 (3) ◽  
pp. 283 ◽  
Author(s):  
José Antonio Esparza Isasa ◽  
Peter Gorm Larsen ◽  
Finn Overgaard Hansen

Sign in / Sign up

Export Citation Format

Share Document