Abstract
Fast-growing cloud computing has a mass impact on power consumption in datacenters. In our previous study, we presented a power-saving method for cloud storage systems, where the stored data were periodically rearranged in a disk array in the order of access frequency. The disk containing unpopular files can often be switched to power-saving mode, enabling power conservation. However, if such unpopular files became popular at some point, the disk containing those files spin up that leads to increase power consumption. To remedy this drawback, in this paper, we present a multi-tier power-saving method for cloud storage systems. The idea behind our method is to divide the disk array into multiple tiers. The first tier containing popular files is always active for fast response, while lower tiers pack unpopular files for power conservation. To maintain such a hierarchical structure, files are periodically migrated to the neighboring tiers according to the access frequency. To evaluate the effectiveness of our proposed method, we measured the performance in simulations and a prototype implementation using real access traces of approximately 60,000 time-series images with a duration of 3,000 h. In the experiments, we observed that our method consumed approximately 22% less energy than the system without any file migration among disks. At the same time, our method maintained a preferred response time with an overall average of 86 ms based on our prototype implementation.
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References
Boru, D., Kliazovich, D., Granelli, F., Bouvry, P., Zomaya, A.Y.: Energy-efficient data replication in cloud computing datacenters. Cluster Comput. 18(1), 385–402 (2015). https://doi.org/10.1007/s10586-014-0404-x
Bostoen, T., Mullender, S., Berbers, Y.: Power-reduction techniques for data-center storage systems. ACM Comput. Surv. (CSUR) 45(3), 33 (2013)
Colarelli, D., Grunwald, D.: Massive arrays of idle disks for storage archives. In: SC 2002: Proceedings of the 2002 ACM/IEEE Conference on Supercomputing, pp. 47–47. IEEE (2002)
E. Pinheiro, R.B., Dubnicki, C.: Exploiting redundancy to conserve energy in storage systems. In: Proceedings ACM SIGMETRICS Conference on Measurement and Modeling of Computer Systems, pp. 15–26 (2006)
Kaushik, R.T., Bhandarkar, M.: Greenhdfs: towards an energy-conserving, storage-efficient, hybrid Hadoop compute cluster. In: Proceedings of the USENIX Annual Technical Conference, vol. 109, p. 34 (2010)
Khosla, A., Das Sarma, A., Hamid, R.: What makes an image popular? In: Proceedings of the 23rd International Conference on World Wide Web, pp. 867–876. ACM (2014)
Kliazovich, D., Bouvry, P., Khan, S.U.: Greencloud: a packet-level simulator of energy-aware cloud computing data centers. J. Supercomput. 62(3), 1263–1283 (2012). https://doi.org/10.1007/s11227-010-0504-1
M. Storer, K. Greenan, E.M., Voruganti, K.: Pergamum: replacing tape with energy efficient reliable, disk-based archival storage. In: Proceedings USENIX Conference on File and Storage Technologies (2008)
Okoshi, J., Hasebe, K., Kato, K.: Power-saving in storage systems for internet hosting services with data access prediction. In: 2013 International Green Computing Conference Proceedings, pp. 1–10. IEEE (2013)
Pinheiro, E., Bianchini, R.: Energy conservation techniques for disk array-based servers. In: Proceedings of the 18th Annual International Conference on Supercomputing, pp. 68–78. ACM (2004)
Zhu, Q., Chen, Z., Tan, L., Zhou, Y., Keeton, K., Wilkes, J.: Hibernator: helping disk arrays sleep through the winter. In: Proceedings ACM symposium on Operating Systems Principles, pp. 177–190 (2005)
Gurumurthi, S., Sivasubramaniam, A., Kandemir, M., Franke, H.: DRPM: dynamic speed control for power management in server class disks. In: ACM SIGARCH Computer Architecture News (2003)
Shehabi, A., et al.: United states data center energy usage report (2016)
Trzciński, T., Rokita, P.: Predicting popularity of online videos using support vector regression. IEEE Trans. Multimedia 19(11), 2561–2570 (2017)
Weddle, C., Oldham, M., Qian, J., Wang, A.I.A., Reiher, P., Kuenning, G.: PARAID: a gear-shifting power-aware RAID. ACM Trans. Storage (TOS) 3(3), 13 (2007)
Yao, X., Wang, J.: RIMAC: a novel redundancy-based hierarchical cache architecture for energy efficient, high performance storage systems. In: Proceedings ACM SIGOPS/EuroSys European Conference on Computer Systems, pp. 249–262 (2006)
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Choeng, H., Hasebe, K., Abe, H., Kato, K. (2020). Multi-tier Power-Saving Method in Cloud Storage Systems for Content Sharing Services. In: Djemame, K., Altmann, J., Bañares, J.Á., Agmon Ben-Yehuda, O., Stankovski, V., Tuffin, B. (eds) Economics of Grids, Clouds, Systems, and Services. GECON 2020. Lecture Notes in Computer Science(), vol 12441. Springer, Cham. https://doi.org/10.1007/978-3-030-63058-4_13
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