Study on target machine selection for Efficient Multi-Migration in Distributed cloud computing

다국어 초록 (Multilingual Abstract)

Cloud computing has recently received considerable attention in both academic and industrial community as a new computing paradigm to provide dynamically scalable and virtualized resource as a service over the Internet. Recently, customer demand for cloud services is a growing in the world. In order to respond to customer demand increases, builds the data centers in multiple locations.
Live migration allows a server administrator to move a running virtual machine or application between different physical machines without disconnecting the client or application. Live migration holds many benefits such as energy saving, load balancing, maintenance.
In thesis propose improvement migration method in lightweight environment through resource monitoring in performance degradation situation like hotspot.
The limited resources significantly impede the improvement of service qualities. Live migration technologies can contribute to efficient resource management in a cloud datacenter. The goal is to overcome to maximize the migration efficiency and maintenance. However, most of the previous works concentrates on the implementation of migration technology itself while previous works didn’t consider waiting time on migration efficiency and live migration such as migration failures due to the insufficient resources in target machine. Nowdays, datacenters are distributed data center rather than a single data center. thus user want to get seamless service.
It is proposed method for seamless service Even if the used service moves to different area in distributed cloud computing.
We conclude with a discussion of research problems in the area. In the future, we will study on live migration mechanism to improve the live migration efficiency in the large-scale service and variety of datacenter environments.

목차 (Table of Contents)

• 1. Introduction 1
• 1.1 Background 1
• 1.2 Research goal and scope 5
• 1.3 Organization of Thesis 6
• 2. related work 7
• 2.1 live migration 7
• 2.2 Openstack 11
• 2.3 Libvirt 13
• 2.4 Docker 14
• 3. proposed architecture and design 15
• 3.1 proposed architecture 15
• 3.2 considered elements 18
• 3.3 migration phase 19
• 4. performance analysis and evaluation 24
• 4.1 experimental environment 24
• 4.2 Performance for Openstack 25
• 4.3 comparison of lightweight environment 29
• 4.4 Performance according to the waiting time 30
• 4.5 performance analysis in distributed environment 33
• 4.6 comparison of performance in docker 35
• 5. Conclusion 37
• Reference 39