Modeling a dynamic data replication strategy to increase system availability in cloud computing environments


Autoria(s): Sun, Da-Wei; Chang, Gui-Ran; Gao, Shang; Jin, Li-Zhong; Wang, Xing-Wei
Data(s)

01/03/2012

Resumo

Failures are normal rather than exceptional in the cloud computing environments. To improve system avai-lability, replicating the popular data to multiple suitable locations is an advisable choice, as users can access the data from a nearby site. This is, however, not the case for replicas which must have a fixed number of copies on several locations. How to decide a reasonable number and right locations for replicas has become a challenge in the cloud computing. In this paper, a dynamic data replication strategy is put forward with a brief survey of replication strategy suitable for distributed computing environments. It includes: 1) analyzing and modeling the relationship between system availability and the number of replicas; 2) evaluating and identifying the popular data and triggering a replication operation when the popularity data passes a dynamic threshold; 3) calculating a suitable number of copies to meet a reasonable system byte effective rate requirement and placing replicas among data nodes in a balanced way; 4) designing the dynamic data replication algorithm in a cloud. Experimental results demonstrate the efficiency and effectiveness of the improved system brought by the proposed strategy in a cloud.

Identificador

http://hdl.handle.net/10536/DRO/DU:30047066

Idioma(s)

eng

Publicador

Springer

Relação

http://dro.deakin.edu.au/eserv/DU:30047066/gao-modelingadynamic-2012.pdf

http://dx.doi.org/10.1007/s11390-012-1221-4

Direitos

2012, Springer Science+Business Media, LLC & Science Press

Palavras-Chave #cloud computing #high fault tolerance #replication perspective #system availability #temporal locality
Tipo

Journal Article