Scalia: An adaptive scheme for efficient multi-cloud storage

A growing amount of data is produced daily resulting in a growing demand for storage solutions. While cloud storage providers offer a virtually infinite storage capacity, data owners seek geographical and provider diversity in data placement, in order to avoid vendor lock-in and to increase availabi...

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Bibliographic Details
Published in2012 International Conference for High Performance Computing, Networking, Storage and Analysis pp. 1 - 10
Main Authors Papaioannou, Thanasis G., Bonvin, Nicolas, Aberer, Karl
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.11.2012
Subjects
Availability
Bandwidth
Cloud computing
Distributed databases
Engines
History
Optimization
Online AccessGet full text
ISBN1467308056
9781467308052
ISSN2167-4329
DOI10.1109/SC.2012.101

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Summary:A growing amount of data is produced daily resulting in a growing demand for storage solutions. While cloud storage providers offer a virtually infinite storage capacity, data owners seek geographical and provider diversity in data placement, in order to avoid vendor lock-in and to increase availability and durability. Moreover, depending on the customer data access pattern, a certain cloud provider may be cheaper than another. In this paper1, we introduce Scalia, a cloud storage brokerage solution that continuously adapts the placement of data based on its access pattern and subject to optimization objectives, such as storage costs. Scalia efficiently considers repositioning of only selected objects that may significantly lower the storage cost. By extensive simulation experiments, we prove the cost-effectiveness of Scalia against static placements and its proximity to the ideal data placement in various scenarios of data access patterns, of available cloud storage solutions and of failures.
ISBN:1467308056
9781467308052
ISSN:2167-4329
DOI:10.1109/SC.2012.101