Issue No. 02 - April-June (2018 vol. 6)
Dong Yuan , School of Electrical and Information Engineering, University of Sydney, Sydney, NSW, Australia
Lizhen Cui , School of Computer Science and Technology, Shandong University, Jinan, Shandong, China
Wenhao Li , School of Computer Science and Technology, Shandong University, Jinan, Shandong, China
Xiao Liu , School of Information Technology, Deakin University, Burwood, Australia
Yun Yang , School of Computer Science and Technology, Anhui University, Hefei, Anhui, China
The proliferation of cloud computing allows users to flexibly store, re-compute or transfer large generated datasets with multiple cloud service providers. However, due to the pay-as-you-go model, the total cost of using cloud services depends on the consumption of storage, computation and bandwidth resources which are three key factors for the cost of IaaS-based cloud resources. In order to reduce the total cost for data, given cloud service providers with different pricing models on their resources, users can flexibly choose a cloud service to store a generated dataset, or delete it and choose a cloud service to regenerate it whenever reused. However, finding the minimum cost is a complicated yet unsolved problem. In this paper, we propose a novel algorithm that can calculate the minimum cost for storing and regenerating datasets in clouds, i.e., whether datasets should be stored or deleted, and furthermore where to store or to regenerate whenever they are reused. This minimum cost also achieves the best trade-off among computation, storage and bandwidth costs in multiple clouds. Comprehensive analysis and rigid theorems guarantee the theoretical soundness of the paper, and general (random) simulations conducted with popular cloud service providers’ pricing models demonstrate the excellent performance of our approach.
Bandwidth, Finite element analysis, Cloud computing, Computational modeling, Data models, Algorithm design and analysis, Benchmark testing
D. Yuan, L. Cui, W. Li, X. Liu and Y. Yang, "An Algorithm for Finding the Minimum Cost of Storing and Regenerating Datasets in Multiple Clouds," in IEEE Transactions on Cloud Computing, vol. 6, no. 2, pp. 519-531, 2018.