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Cost-optimized redundant data storage in the cloud
Publikationstyp
Conference Paper
Date Issued
2017-12-01
Sprache
English
Volume
11
Issue
4
Start Page
411
End Page
426
Citation
Service Oriented Computing and Applications 11 (4): 411-426 (2017-12-01)
Publisher DOI
Scopus ID
The use of cloud-based storage systems for storing data is a popular alternative to local storage systems. Beside several benefits of cloud-based storages, there are also downsides like vendor lock-in or unavailability. Moreover, the selection of the best fitting storage solution can be a tedious and cumbersome task and the storage requirements may change over time. In this paper, we formulate a system model that uses multiple cloud-based services to realize a redundant and cost-efficient storage. Within this system model, we formulate a local and a global optimization problem that considers historical data access information and predefined quality of service requirements to select a cost-efficient storage solution. Furthermore, we present a heuristic optimization approach for the global optimization. Extensive evaluations show the benefits of our work in comparison with a baseline that follows a state-of-the-art approach. We show that our solutions save up to 30% of the cumulative cost in comparison with the baseline.
Subjects
Cloud storage
Erasure coding
Global optimization
Long-term storage
MILP
Redundant storage
Vendor lock-in