Go to page

Bibliographic Metadata

Cost-optimized redundant data storage in the cloud
AuthorWaibel, Philipp ; Matt, Johannes ; Hochreiner, Christoph ; Skarlat, Olena ; Hans, Ronny ; Schulte, Stefan
Published in
Service Oriented Computing and Applications, 2017, Vol. 11, Issue 4, page 411-426
PublishedSpringer London, 2017
Document typeJournal Article
Keywords (EN)Cloud storage / Redundant storage / Erasure coding / Vendor lock-in / Long-term storage / Global optimization / MILP
Project-/ReportnumberCommission of the European Union - CREMA H2020-RIA project: 637066)
URNurn:nbn:at:at-ubtuw:3-4392 Persistent Identifier (URN)
 The work is publicly available
Cost-optimized redundant data storage in the cloud [0.64 mb]
Abstract (English)

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.

The PDF-Document has been downloaded 8 times.
CC-BY-License (4.0)Creative Commons Attribution 4.0 International License