CBase: Fast Virtual Machine storage data migration with a new data center structure

2019 | journal article; research paper. A publication of Göttingen

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​CBase: Fast Virtual Machine storage data migration with a new data center structure​
Zhang, F.; Liu, G.; Zhao, B.; Kasprzak, P.; Fu, X.   & Yahyapour, R. ​ (2019) 
Journal of Parallel and Distributed Computing124 pp. 14​-26​.​ DOI: 

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Zhang, Fei; Liu, Guangming; Zhao, Bo; Kasprzak, Piotr; Fu, Xiaoming ; Yahyapour, Ramin 
Live Virtual Machine (VM) migration within a data center is an important technology for cloud management, and has brought many benefits to both cloud providers and users. With the development of cloud computing, across-data-center VM migration is also desired. Normally, there is no shared storage system between data centers, hence the storage data (disk image) of a VM will be migrated to the destination data center as well. However, the slow network speed of the Internet and the comparatively large size of VM disk image make VM storage data migration become a bottleneck for live VM migration across data centers. In this paper, based on a detailed analysis of VM deployment models and the nature of VM image data, we design and implement a new migration system, called CBase. The key concept of CBase is a newly introduced central base image repository for reliable and efficient data sharing between VMs and data centers. With this central repository, further performance optimizations to VM storage data migration are made possible. Two migration mechanisms (data deduplication and Peer-to-Peer (P2P) file sharing) are utilized to accelerate base image migration, and a strategy is designed to elevate the synchronization of newly-written disk blocks. The results from an extensive experiment show that CBase significantly outperforms existing migration mechanisms under different conditions regarding total migration time and total network traffic. In particular, CBase with data deduplication is better than P2P file sharing for base image migration in our experimental environment.
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Journal of Parallel and Distributed Computing 
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