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An algorithm for finding the minimum cost of storing and regenerating datasets in multiple clouds

Yuan, Dong, Cui, Lizhen, Li, Wenhao, Liu, Xiao and Yang, Yun 2015, An algorithm for finding the minimum cost of storing and regenerating datasets in multiple clouds, IEEE transactions on cloud computing, vol. PP, no. 99, pp. 1-14, doi: 10.1109/TCC.2015.2491920.

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Title An algorithm for finding the minimum cost of storing and regenerating datasets in multiple clouds
Author(s) Yuan, Dong
Cui, Lizhen
Li, Wenhao
Liu, XiaoORCID iD for Liu, Xiao orcid.org/0000-0002-4151-8522
Yang, Yun
Journal name IEEE transactions on cloud computing
Volume number PP
Issue number 99
Start page 1
End page 14
Total pages 14
Publisher IEEE
Place of publication Piscatawy, N.J.
Publication date 2015-10-16
ISSN 2168-7161
Keyword(s) Cloud Computing
Data Storage and Regeneration
Minimum Cost
Summary 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.
Language eng
DOI 10.1109/TCC.2015.2491920
Field of Research 080599 Distributed Computing not elsewhere classified
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category C1.1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2015, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30088639

Document type: Journal Article
Collection: School of Information Technology
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