Abstract
Cloud storage systems aim to offer cost-effective storage services. The key is sharing resources between multiple users by virtualization technologies. Storage resources in cloud systems can not be reclaimed even when users do not access their data for a long time. Storage resources must be shared through space sharing rather than time sharing. Existing technologies improve storage utilization at various layers and data sets, making it difficult to analyze the efficiency of a cloud storage in a holistic way. To address this problem, we propose an evaluation framework to study the impacts of a wide variety of I/O techniques on an enterprise-scale cloud storage. The framework offers storage utilization evaluation from both the users and the vendors’ perspective.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Hilbert, M., López, P.: The worlds technological capacity to store, communicate, and compute information. Science 332(6025), 60–65 (2011)
Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C., Byers, A.H.: Big data: The next frontier for innovation, competition, and productivity. McKinsey Global Institute, pp. 1–137 (2011)
Twinstrata: Economics of public cloud storage. http://pt.slideshare.net/rinfantino/the-economics-of-public-cloud-storage
Li, X., Li, Y., Liu, T., Qiu, J., Wang, F.: The method and tool of cost analysis for cloud computing. In: IEEE International Conference on Cloud Computing, CLOUD’09, pp. 93–100. IEEE (2009)
Greenberg, A., Hamilton, J., Maltz, D.A., Patel, P.: The cost of a cloud: research problems in data center networks. ACM SIGCOMM Comput. Commun. Rev. 39(1), 68–73 (2008)
Colarelli, D., Grunwald, D.: Massive arrays of idle disks for storage archives. In: Proceedings of the 2002 ACM/IEEE Conference on Supercomputing, pp. 1–11. IEEE Computer Society Press (2002)
Pinheiro, E., Bianchini, R.: Energy conservation techniques for disk array-based servers. In: International Conference on Supercomputing: Proceedings of the 18th Annual International Conference on Supercomputing, vol. 26, pp. 68–78 (2004)
Manzanares, A., Ruan, X., Yin, S., Xie, J., Ding, Z., Tian, Y., Majors, J., Qin, X.: Energy efficient prefetching with buffer disks for cluster file systems. In: 2010 39th International Conference on Parallel Processing (ICPP), pp. 404–413. IEEE (2010)
Alvarez, G.A., Borowsky, E., Go, S., Romer, T.H., Becker-Szendy, R., Golding, R., Merchant, A., Spasojevic, M., Veitch, A., Wilkes, J.: Minerva: an automated resource provisioning tool for large-scale storage systems. ACM Trans. Comput. Syst. (TOCS) 19(4), 483–518 (2001)
Anderson, E., Hobbs, M., Keeton, K., Spence, S., Uysal, M., Veitch, A.: Hippodrome: running circles around storage administration. In: Proceedings of the Conference on File and Storage Technologies, pp. 175–188 (2002)
Cao, Y., Chen, C., Guo, F., Jiang, D., Lin, Y., Ooi, B.C., Vo, H.T., Wu, S., Xu, Q.: A cloud data storage system for supporting both oltp and olap. In: IEEE 27th International Conference on Data Engineering (ICDE), pp. 291–302. IEEE (2011)
Lillibridge, M., Eshghi, K., Bhagwat, D., Deolalikar, V., Trezise, G., Camble, P.: Sparse indexing: large scale, inline deduplication using sampling and locality. In: Proccedings of the 7th Conference on File and Storage Technologies, pp. 111–123 (2009)
Wallace, G., Douglis, F., Qian, H., Shilane, P., Smaldone, S., Chamness, M., Hsu, W.: Characteristics of backup workloads in production systems. In: Proceedings of the Tenth USENIX Conference on File and Storage Technologies (FAST12) (2012)
Acknowledgment
This work was supported by the National High-tech R&D Program of China (863 Program) under Grant No. 2013AA01A215 and No. 2012AA011004; the NFS of China under Grant No. 61033007; the NFS of China under Grant No. 61272123 and No. 61303037.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Zhang, X., Guo, W., Li, Z., Zhao, X., Qin, X. (2014). A Framework to Measure Storage Utilization in Cloud Storage Systems. In: Han, WS., Lee, M., Muliantara, A., Sanjaya, N., Thalheim, B., Zhou, S. (eds) Database Systems for Advanced Applications. DASFAA 2014. Lecture Notes in Computer Science(), vol 8505. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-43984-5_13
Download citation
DOI: https://doi.org/10.1007/978-3-662-43984-5_13
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-43983-8
Online ISBN: 978-3-662-43984-5
eBook Packages: Computer ScienceComputer Science (R0)