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Frugal storage for cloud file systems

Published: 10 April 2012 Publication History

Abstract

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.

References

[1]
Amazon. EBS to S3 Snapshot Block Size. https://forums.aws.amazon.com/message.jspa?messageID =142082.
[2]
Amazon. Elastic block store. http://aws.amazon.com/ebs/.
[3]
Amazon. Elasticache. http://aws.amazon.com/elasticache/.
[4]
Amazon. Simple storage service faqs. http://aws.amazon.com/s3/faqs/.
[5]
Azure. Caching service. http://msdn.microsoft.com/en-us/library/windowsazure/gg278356.aspx.
[6]
S.-H. Gary Chan and F. A. Tobagi. Modeling and dimensioning hierarchical storage systems for low-delay video services. IEEE Transactions on Computers, 52, July 2003.
[7]
D. Isaac. Hierarchical storage management for relational databases. In Symposium on Mass Storage Systems, 1993.
[8]
A. Karlin, M. Manasse, L. McGeoch, and S. Owicki. Competitive randomized algorithms for non-uniform problems. In Proc. of ACM-SIAM Symposium on Discrete Algorithms (SODA), 1990.
[9]
A. W. Leung, S. Pasupathy, G. Goodson, and E. L. Miller. Measurement and analysis of large-scale network file system workloads. In Proc. of the USENIX (ATC) Annual Technical Conference, 2008.
[10]
N. Megiddo and D. Modha. Arc: A self-tuning,. low overhead replacement cache. In Proceedings of the USENIX Conference on (FAST) File and Storage Technologies, 2003.
[11]
D. Narayanan, A. Donnelly, and A. Rowstron. MSR Cambridge Traces. http://iotta.snia.org/traces/388.
[12]
D. Narayanan, A. Donnelly, and A. Rowstron. Write off-loading: practical power management for enterprise storage. In Proceedings of the USENIX Conference on (FAST) File and Storage Technologies, 2008.
[13]
S3-EBS. Amazon's Elastic Block Store explained. http://blog.rightscale.com/2008/08/20/amazon-ebs-explained/.
[14]
S3Backer. FUSE-based single file backing store via Amazon S3. http://code.google.com/p/s3backer/wiki/ChoosingBlockSize.
[15]
Wikipedia. Hierarchical storage management. http://en.wikipedia.org/wiki/Hierarchical_storage_management.
[16]
J. Wilkes, R. Golding, C. Staelin, and T. Sullivan. The hp autoraid hierarchical storage system. ACM Transactions on Computer Systems, 14, Feb 1996.

Cited By

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  • (2024)SVD: A Scalable Virtual Machine Disk FormatIEEE Transactions on Cloud Computing10.1109/TCC.2024.339139012:2(684-696)Online publication date: Apr-2024
  • (2023)InfiniStore: Elastic Serverless Cloud StorageProceedings of the VLDB Endowment10.14778/3587136.358713916:7(1629-1642)Online publication date: 1-Mar-2023
  • (2023)PackCache: An Online Cost-Driven Data Caching Algorithm in the CloudIEEE Transactions on Computers10.1109/TC.2022.319196972:4(1208-1214)Online publication date: 1-Apr-2023
  • Show More Cited By

Recommendations

Reviews

David Bruce Henderson

Typical modern physical storage systems have a hierarchy of several tiers of storage, with data moving automatically between the various tiers depending on the frequency of access to the data. Fast but expensive storage is used for data that needs to be accessed quickly and frequently, while slower but less expensive storage is used for data that doesn't experience frequent access. The authors of this paper have developed a framework for applying this hierarchical storage strategy to cloud storage services. The authors present a short introduction to hierarchical storage, summarize related works, and then make their proposition. Basically, they contend that significant cost advantages can be achieved through a hierarchical structuring of multiple cloud storage offerings with different cost/performance characteristics. They present their frugal cloud file system (FCFS) as a solution and demonstrate its effectiveness using the pricing of Amazon's cloud service offerings. Cloud-based storage has a significant advantage over physical storage alternatives in that the size of the various tiers of storage can be dynamic rather than fixed. The proposed solution integrates multiple storage services and dynamically adapts the storage volume sizes of each service to improve cost effectiveness. The paper explains the solution at a high level, illustrated with graphs and figures. The authors then lay out their dynamic storage framework and two schemes for determining when and how to dynamically move data between the different storage tiers. The authors provide the results of simulations using real-life disk traces from a medium-sized data center to support their claims of cost effectiveness. The paper is supported by figures and associated cost examples that will be useful to those actively considering cloud storage as a strategic solution. A tiered hierarchical strategy for cloud storage seems intuitively to be a winner, just as hierarchical tiered physical storage was before it. All that is needed now is for someone to offer FCFS as a cloud service. Online Computing Reviews Service

Michael G. Murphy

As more and more enterprises look to cloud storage to meet their data storage needs at a lower cost of operation, this issue is of important practical significance. In this paper, Puttaswamy et al. address cost-effective cloud storage. They propose a frugal cloud file system (FCFS), a storage management application designed to reduce operating costs in the cloud. Specific comparisons are made to Amazon's Elastic Block Store (EBS), Simple Storage Service (S3), and ElastiCache, which represent of a variety of cloud storage options. The major tradeoff is between storage and access costs. Dynamically managing this tradeoff with products that emphasize one factor or the other offers significant overall cost savings. The first section provides a conceptual introduction, a summary of related work, and the authors' view of what this paper contributes to the field. Subsequent sections provide a motivating framework for dynamic storage; a careful description of FCFS; cost optimization algorithms, including cost analysis; experimental design and the nature of the real-life traces used; an evaluation of the results; and concluding thoughts. Twelve figures, three tables, and pseudocode for block reads in FCFS effectively complement the text. The paper is interesting and insightful within the constraints noted by the authors. It will be interesting to see whether significant contributions based on actual implementations are made to the literature on cloud storage, since such a report tends to become a postmortem after the technology moves forward and the older technology has lost its proprietary advantage. Online Computing Reviews Service

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Published In

cover image ACM Conferences
EuroSys '12: Proceedings of the 7th ACM european conference on Computer Systems
April 2012
394 pages
ISBN:9781450312233
DOI:10.1145/2168836
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 10 April 2012

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Author Tags

  1. caching
  2. cloud computing
  3. storage
  4. storage cost

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EuroSys '12
Sponsor:
EuroSys '12: Seventh EuroSys Conference 2012
April 10 - 13, 2012
Bern, Switzerland

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Overall Acceptance Rate 241 of 1,308 submissions, 18%

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Twentieth European Conference on Computer Systems
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Cited By

View all
  • (2024)SVD: A Scalable Virtual Machine Disk FormatIEEE Transactions on Cloud Computing10.1109/TCC.2024.339139012:2(684-696)Online publication date: Apr-2024
  • (2023)InfiniStore: Elastic Serverless Cloud StorageProceedings of the VLDB Endowment10.14778/3587136.358713916:7(1629-1642)Online publication date: 1-Mar-2023
  • (2023)PackCache: An Online Cost-Driven Data Caching Algorithm in the CloudIEEE Transactions on Computers10.1109/TC.2022.319196972:4(1208-1214)Online publication date: 1-Apr-2023
  • (2022)UFC2: User-Friendly Collaborative CloudIEEE Transactions on Parallel and Distributed Systems10.1109/TPDS.2021.313249633:9(2163-2182)Online publication date: 1-Sep-2022
  • (2020)INFINICACHEProceedings of the 18th USENIX Conference on File and Storage Technologies10.5555/3386691.3386717(267-282)Online publication date: 24-Feb-2020
  • (2020)Emerging Ontology Formulation of Optimized Internet of Things (IOT) Services with Cloud ComputingSoft Computing: Theories and Applications10.1007/978-981-15-0751-9_4(31-52)Online publication date: 11-Feb-2020
  • (2019)Transparent Throughput Elasticity for Modern Cloud StorageApplying Integration Techniques and Methods in Distributed Systems and Technologies10.4018/978-1-5225-8295-3.ch007(156-191)Online publication date: 2019
  • (2019)Waveform Signal Entropy and Compression Study of Whole-Building Energy DatasetsProceedings of the Tenth ACM International Conference on Future Energy Systems10.1145/3307772.3328285(58-67)Online publication date: 15-Jun-2019
  • (2019)Popularity-Aware Multi-Failure Resilient and Cost-Effective Replication for High Data Durability in Cloud StorageIEEE Transactions on Parallel and Distributed Systems10.1109/TPDS.2018.287338430:10(2355-2369)Online publication date: 1-Oct-2019
  • (2019)Cost Optimization for Dynamic Replication and Migration of Data in Cloud Data CentersIEEE Transactions on Cloud Computing10.1109/TCC.2017.26597287:3(705-718)Online publication date: 1-Jul-2019
  • Show More Cited By

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