Dataset replica placement strategy under a response time constraint in the cloud

In cloud computing environment, especially data-intensive systems, large amounts of datasets are stored in distributed data centres, and are often retrieved by users in different regions. To reduce the users' response time, replicating the popular datasets to multiple suitable data centres is an advisable choice, as tasks can access the datasets from a nearby site. Nevertheless, the dataset replicas' suitable storage placement selection is still an important issue that should be solved urgently from the response time constraint view, for the reason that too many replicas are infeasible in practice. In this paper, we first propose a comprehensive dataset response time estimation model, then present a replica placement model based on Steiner tree. After that, an approximate replica placement algorithm under a response time constraint in the cloud is given using Kruskal minimum spanning tree. At last, a practical and reasonable performance evaluation is designed and implemented. Both the theoretical analysis and simulations conducted on general (random) datasets show the efficiency and effectiveness of the proposed strategy in the cloud.