摘要
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.
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.
基金
Supported by the National Natural Science Foundation of China under Grant Nos. 61070162, 71071028 and 70931001
the Specialized Research Fund for the Doctoral Program of Higher Education of China under Grant Nos. 20110042110024 and 20100042110025
the Fundamental Research Funds for the Central Universities of China under Grant Nos. N100604012, N090504003 and N090504006
