Abstract
Energy consumption has become a first-class optimization goal in design and implementation of data-intensive computing systems. This is particularly true in the design of database management system (DBMS), which was found to be the major consumer of energy in the software stack of modern data centers. Among all database components, the storage system is the most power-hungry element. In this paper, we present our research on designing a power-aware data storage system. To tackle the limitations of the previous work, we introduce a DPM optimization model to minimize power consumption of the disk-based storage system while satisfying given performance requirements. It dynamically determines the state of disks and plans for inter-disk fragment migration to achieve desirable balance between power consumption and query response time. We evaluate our proposed idea by running simulations using several synthetic workloads based on popular TPC benchmarks.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
http://www.nrdc.org/energy/data-center-efficiency-assessment.asp
Gurumurthi, S., Sivasubramaniam, A., Kandemir, M., Franke, H.: Reducing disk power consumption in servers with DRPM. J. Comput. 36(12), 59–66 (2003)
Poess, M., Nambiar, R.O.: Energy cost, the key challenge of today’s data centers: a power consumption analysis of tpc-c results. In: VLDB 2008 Proceedings. ACM Press (2008)
Moore, F.: more power needed. In: Energy User News, November 2002
www.hgst.com/hard-drives/enterprise-hard-drives/enterprise-sas-drives/ultrastar-7k6000
Zhu, Q., Zhou, Y.: Power-aware storage cache management. IEEE Trans. Comput. 54(5), 587–602 (2005)
Papathanasiou, A.E., Scott, M.L.: Energy efficient prefetching and caching. In: USENIX Annual Technical Conference, Boston (2004)
Li, D., Wang, J.: Eeraid: power efficient redundant and inexpensive disk arrays. In: 11th Workshop on SIGOPS European Workshop, Belgium (2004)
Yao, X., Wang, J.: RIMAC: a novel redundancy-based hierarchical cache architecture for energy efficient, high performance storage systems. In: ACM SIGOPS OS Review (2006)
Zhu, Q., David, F.M., Devaraj, C.F., Li, Z., Zhou, Y., Cao, P.: Reducing energy consumption of disk storage using power-aware cache management. In: IEEE Proceedings of Software (2004)
Pinheiro, E., Bianchini, R.: Energy conservation techniques for disk array-based servers. In: Proceedings of ICS 2004 (2004)
Colarelli, D., Grunwald, D.: Massive arrays of idle disks for storage archives. In: ACM/IEEE Conference on Supercomputing, pp. 1–11 (2002)
Weddle, C., Oldham, M., Qian, J., Wang, A., Reiher, P., Kuenning, G.: PARAID: A gear-shifting power-aware RAID. ACM Trans. Storage (TOS) 3(3) (2007). 13
Verma, A., Koller, R., Useche, L., Rangaswami, R.: SRCMap: energy proportional storage using dynamic consolidation. In: Proceedings of FAST 10, vol. 10
Otoo, E., Rotem, D., Tsao, S.-C.: Dynamic data reorganization for energy savings in disk storage systems. In: Gertz, M., Ludäscher, B. (eds.) SSDBM 2010. LNCS, vol. 6187, pp. 322–341. Springer, Heidelberg (2010)
Guerra, J., Pucha, H., Glider, J., Belluomini, W., Rangaswami, R.: Cost effective storage using extent based dynamic tiering. In: Proceedings of FAST, pp. 273–286 (2011)
Zhu, Q., Chen, Z., Tan, L., Zhou, Y., Keeton, K., Wilkes, J.: Hibernator: helping disk arrays sleep through the winter. In: ACM SIGOPS Operating Systems Review (2005)
Garcia, C.E., Prett, D.M., Morari, M.: Model predictive control: theory and practice- a survey. In: Automatica 1989
Behzadnia, P., Tu, Y.-C., Zeng, B., Yuan, W., Wang, X.: Dynamic Power-Aware Disk Storage Management in Database Server. Technical report CSE/15-123., Department of Computer Science and Engineering, University of South Florida (2015). http://msdb.csee.usf.edu/E2DBMS/tech-report-123.pdf
Kim, J., Chou, J., Rotem, D.: iPACS: power-aware covering sets for energy proportionality and performance in data parallel computing clusters. J. Parallel Distrib. Comput. Elsevier 74(1), 1762–1774 (2014)
Kim, J., Chou, J., Rotem, D.: Energy proportionality and performance in data parallel computing clusters. In: 23rd SSDBM Conference, July 2011
Chou, J., Kim, J., Rotem, D.: Energy-aware scheduling in disk storage systems. In: Proceedings of ICDCS 2011 (2011)
The SDSS DR1 SkyServer. http://skyserver.sdss.org/dr1/en/skyserver/paper/
Nicola, M., Jarke, M.: Performance modeling of distributed and replicated databases. IEEE Trans. Knowl. Data Eng. (TKDE) 12(4), 645–672 (2000)
http://cepac.cheme.cmu.edu/pasilectures/lee/LecturenoteonMPC-JHL.pdf
Acknowledgments
The project described was supported by grants IIS-1117699 and IIS-1156435 from the National Science Foundation (NSF) of USA. Equipments used in the experiments are partially supported by a grant (CNS-1513126) from NSF.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Behzadnia, P., Yuan, W., Zeng, B., Tu, YC., Wang, X. (2016). Dynamic Power-Aware Disk Storage Management in Database Servers. In: Hartmann, S., Ma, H. (eds) Database and Expert Systems Applications. DEXA 2016. Lecture Notes in Computer Science(), vol 9828. Springer, Cham. https://doi.org/10.1007/978-3-319-44406-2_25
Download citation
DOI: https://doi.org/10.1007/978-3-319-44406-2_25
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-44405-5
Online ISBN: 978-3-319-44406-2
eBook Packages: Computer ScienceComputer Science (R0)