The HP AutoRAID hierarchical storage system
ACM Transactions on Computer Systems (TOCS) - Special issue on operating system principles
Competitive randomized algorithms for non-uniform problems
SODA '90 Proceedings of the first annual ACM-SIAM symposium on Discrete algorithms
Modeling and Dimensioning Hierarchical Storage Systems for Low-Delay Video Services
IEEE Transactions on Computers
Write off-loading: practical power management for enterprise storage
FAST'08 Proceedings of the 6th USENIX Conference on File and Storage Technologies
Measurement and analysis of large-scale network file system workloads
ATC'08 USENIX 2008 Annual Technical Conference on Annual Technical Conference
ARC: a self-tuning, low overhead replacement cache
FAST'03 Proceedings of the 2nd USENIX conference on File and storage technologies
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Enterprises are moving their IT infrastructure to cloud service providers with the goal of saving costs and simplifying management overhead. One of the critical services for any enterprise is its file system, where users require real-time access to files. Cloud service providers provide several building blocks such as Amazon EBS, or Azure Cache, each with very different pricing structures that differ on the basis of storage, access and bandwidth costs. Moving an entire file system to the cloud using such services is not cost-optimal if we rely on only one of these services. In this paper, we propose FCFS, a storage solution that drastically reduces the cost of operating a file system in the cloud. Our solution integrates multiple storage services and dynamically adapts the storage volume sizes of each service to provide a cost-efficient solution with provable performance bounds. Using real-world large scale data sets spanning a variety of work loads from an enterprise data center, we show that FCFS can reduce file storage and access costs in current cloud services by a factor of two or more, while allowing users to utilize the benefits of the various cloud storage services.