Impact of Hybrid Virtualization Using VM and Container on Live Migration and Cloud Performance

2018 ◽  
pp. 196-208
Author(s):  
Oussama Smimite ◽  
Karim Afdel
Keyword(s):  
Live Migration

Improved Post-Copy Live Migration with Memory Page Prefetching

2020 ◽  
Vol 16 (5) ◽  
pp. 728
Author(s):  
Cui Yong ◽  
Chen Haoran ◽  
Zhu Liang
Keyword(s):  
Live Migration ◽  
With Memory

An Experimental Study on Virtual Machine Live Migration Impact on Services Performance

2019 ◽  
Vol 38 (2) ◽  
pp. 291-320
Author(s):  
Petrônio Bezerra ◽  
Marcela Santos ◽  
Edlane Alves ◽  
Anderson Costa ◽  
Fellype Albuquerque ◽  
...  
Keyword(s):  
Experimental Study ◽  
Virtual Machine ◽  
Live Migration ◽  
Virtual Machine Live Migration

Study on virtual machine’s live migration

2009 ◽  
Vol 28 (9) ◽  
pp. 2375-2377 ◽  
Author(s):  
Xue JIANG ◽  
Xiao-yong LI
Keyword(s):  
Live Migration

scholarly journals Swarm-Like Distributed Algorithm for Scheduling a Microservice-Based Application to the Cloud Servers

Electronics ◽  
2021 ◽  
Vol 10 (13) ◽  
pp. 1553
Author(s):  
Marian Rusek ◽  
Grzegorz Dwornicki
Keyword(s):  
Distributed Applications ◽  
Practical Implementation ◽  
Live Migration ◽  
Cloud Infrastructure ◽  
Application Development ◽  
Cloud Management ◽  
Cloud Application ◽  
Cloud Servers ◽  
Distributed Cloud ◽  
Better Than

Introduction of virtualization containers and container orchestrators fundamentally changed the landscape of cloud application development. Containers provide an ideal way for practical implementation of microservice-based architecture, which allows for repeatable, generic patterns that make the development of reliable, distributed applications more approachable and efficient. Orchestrators allow for shifting the accidental complexity from inside of an application into the automated cloud infrastructure. Existing container orchestrators are centralized systems that schedule containers to the cloud servers only at their startup. In this paper, we propose a swarm-like distributed cloud management system that uses live migration of containers to dynamically reassign application components to the different servers. It is based on the idea of “pheromone” robots. An additional mobile agent process is placed inside each application container to control the migration process. The number of parallel container migrations needed to reach an optimal state of the cloud is obtained using models, experiments, and simulations. We show that in the most common scenarios the proposed swarm-like algorithm performs better than existing systems, and due to its architecture it is also more scalable and resilient to container death. It also adapts to the influx of containers and addition of new servers to the cloud automatically.

Live migration improvements by related dirty memory prediction in cloud computing

2017 ◽  
Vol 90 ◽  
pp. 83-89 ◽  
Author(s):  
Tin-Yu Wu ◽  
Nadra Guizani ◽  
Jhih-Siang Huang
Keyword(s):  
Cloud Computing ◽  
Live Migration ◽  
Memory Prediction

No Break of Virtual Network during Live Migration

2010 ◽  
Author(s):  
Xingang Liu ◽  
Jinpeng Huai ◽  
Qin Li ◽  
Tianyu Wo
Keyword(s):  
Virtual Network ◽  
Live Migration
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