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SCHEDULE: NOV 10-16, 2012

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Scalia: An Adaptive Scheme for Efficient Multi-Cloud Storage

SESSION: Cloud Computing

EVENT TYPE: Papers

TIME: 1:30PM - 2:00PM

SESSION CHAIR: Manish Parashar

AUTHOR(S):Thanasis G. Papaioannou, Nicolas Bonvin, Karl Aberer

ROOM:355-D

ABSTRACT:
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 paper, 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 cleverly considers re-positioning 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.

Chair/Author Details:

Manish Parashar (Chair) - Rutgers University

Thanasis G. Papaioannou - EPFL

Nicolas Bonvin - EPFL

Karl Aberer - EPFL

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Scalia: An Adaptive Scheme for Efficient Multi-Cloud Storage

SESSION: Cloud Computing

EVENT TYPE:

TIME: 1:30PM - 2:00PM

SESSION CHAIR: Manish Parashar

AUTHOR(S):Thanasis G. Papaioannou, Nicolas Bonvin, Karl Aberer

ROOM:355-D

ABSTRACT:
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 paper, 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 cleverly considers re-positioning 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.

Chair/Author Details:

Manish Parashar (Chair) - Rutgers University

Thanasis G. Papaioannou - EPFL

Nicolas Bonvin - EPFL

Karl Aberer - EPFL

Add to iCal  Click here to download .ics calendar file

Add to Outlook  Click here to download .vcs calendar file

Add to Google Calendarss  Click here to add event to your Google Calendar