Abstract
We present a power-efficient scheme for erasure-coded storage clusters---ECS2---which aims to offer high energy efficiency with marginal reliability degradation. ECS2 utilizes data redundancies and deferred writes to conserve energy. In ECS2 parity blocks are buffered exclusively in active data nodes whereas parity nodes are placed into low-power mode. (k + r, k) RS-coded ECS2 can achieve ⌈(r + 1)/2⌉-fault tolerance for k active data nodes and r-fault tolerance for all k + r nodes. ECS2 employs the following three optimizing approaches to improve the energy efficiency of storage clusters. (1) An adaptive threshold policy takes system configurations and I/O workloads into account to maximize standby time periods; (2) a selective activation policy minimizes the number of power-transitions in storage nodes; and (3) a region-based buffer policy speeds up the synchronization process by migrating parity blocks in a batch method. After implementing an ECS2-based prototype in a Linux cluster, we evaluated its energy efficiency and performance using four different types of I/O workloads. The experimental results indicate that compared to energy-oblivious erasure-coded storage, ECS2 can save the energy used by storage clusters up to 29.8% and 28.0% in read-intensive and write-dominated workloads when k = 6 and r = 3, respectively. The results also show that ECS2 accomplishes high power efficiency in both normal and failed cases without noticeably affecting the I/O performance of storage clusters.
- Aguilera, M., Janakiraman, R., and Xu, L. 2005. Using erasure codes efficiently for storage in a distributed system. In Proceedings of IEEE International Conference on Dependable Systems and Networks (DSN). 336--345. Google Scholar
Digital Library
- Amur, H., Cipar, J., Gupta, V., Ganger, G., Kozuch, M., and Schwan, K. 2010. Robust and flexible power-proportional storage. In Proceedings of the 1st ACM Symposium on Cloud Computing. 217--228. Google Scholar
Digital Library
- Application, O. 2007. I/O and search engine I/O. umass trace repository. http://traces.cs.umass.edu/.Google Scholar
- Bairavasundaram, L., Goodson, G., Pasupathy, S., and Schindler, J. 2007. An analysis of latent sector errors in disk drives. In Proceedings of the ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems. 289--300. Google Scholar
Digital Library
- Blaum, M., Brady, J., Bruck, J., and Menon, J. 1995. Evenodd: An efficient scheme for tolerating double disk failures in raid architectures. IEEE Trans. Comput. 44, 2, 192--202. Google Scholar
Digital Library
- Borthakur, D. 2008. Hdfs architecture guide. http://hadoop.apache.org/hdfs.Google Scholar
- Borthakur, D. 2010. Hdfs and erasure codes (hdfs-raid).Google Scholar
- Chen, F., Jiang, S., and Zhang, X. 2006. Smartsaver: Turning flash drive into a disk energy saver for mobile computers. In Proceedings of the IEEE International Symposium on Low Power Electronics and Design (ISLPED). 412--417. Google Scholar
Digital Library
- Colarelli, D. and Grunwald, D. 2002. Massive arrays of idle disks for storage archives. In Proceedings of the ACM/IEEE Conference on Supercomputing. 1--11. Google Scholar
Digital Library
- Corbett, P., English, B., Goel, A., Grcanac, T., Kleiman, S., Leong, J., and Sankar, S. 2004. Row-diagonal parity for double disk failure correction. In Proceedings of the 3rd USENIX Conference on File and Storage Technologies (FAST). 1--14. Google Scholar
Digital Library
- Fan, B., Tantisiriroj, W., Xiao, L., and Gibson, G. 2009. Diskreduce: Raid for data-intensive scalable computing. In Proceedings of the 4th Annual Workshop on Petascale Data Storage. 6--10. Google Scholar
Digital Library
- Ganesh, L., Weatherspoon, H., Balakrishnan, M., and Birman, K. 2007. Optimizing power consumption in large scale storage systems. In Proceedings of the 11th USENIX Workshop On Hot Topics In Operating Systems. Google Scholar
Digital Library
- Ghemawat, S., Gobioff, H., and Leung, S. 2003. The Google file system. In Proceedings of the 19th ACM Symposium on Operating Systems Principles. 29--43. Google Scholar
Digital Library
- Greenan, K., Long, D., Miller, E., Schwarz, S., and Wylie, J. 2008. A spin-up saved is energy earned: achieving power-efficient, erasure-coded storage. In Proceedings of the 4th USENIX Conference on Hot Topics in System Principles. 4--10. Google Scholar
Digital Library
- Hafner, J. 2005. Weaver codes: Highly fault tolerant erasure codes for storage systems. In Proceedings of the 4th USENIX Conference on File and Storage Technologies. 211--224. Google Scholar
Digital Library
- Hafner, J. and Rao, K. 2006. Notes on reliability models for non-MDS erasure codes. IBM Res. rep. RJ10391.Google Scholar
- Hafner, J., Pandey, P., and Thakur, T. 2010. Read-modify-write protocol for maintaining parity coherency in a write-back distributed redundancy data storage system. US Patent App. 12/710,123.Google Scholar
- Holland, M., Gibson, G., and Siewiorek, D. 1994. Architectures and algorithms for on-line failure recovery in redundant disk arrays. Distrib. Par. Datab. 2, 3, 295--335. Google Scholar
Digital Library
- Jiang, W., Hu, C., Zhou, Y., and Kanevsky, A. 2008. Are disks the dominant contributor for storage failures?: a comprehensive study of storage subsystem failure characteristics. ACM Trans. Storage 4, 3, 7. Google Scholar
Digital Library
- Kavalanekar, S., Worthington, B., Zhang, Q., and Sharda, V. 2008. Characterization of storage workload traces from production windows servers. In Proceedings of the IEEE International Symposium on Workload Characterization (IISWC). 119--128.Google Scholar
- Lang, W. and Patel, J. 2010. Energy management for mapreduce clusters. Proc. VLDB Endow. 3, 1--2, 129--139. Google Scholar
Digital Library
- Lang, W., Patel, J., and Naughton, J. 2010. On energy management, load balancing and replication. ACM SIGMOD Rec. 38, 4, 35--42. Google Scholar
Digital Library
- Leverich, J. and Kozyrakis, C. 2010. On the energy (in) efficiency of hadoop clusters. ACM SIGOPS Oper. Syst. Rev. 44, 1, 61--65. Google Scholar
Digital Library
- Li, D. and Wang, J. 2004. Eeraid: Energy efficient redundant and inexpensive disk array. In Proceedings of the 11th Workshop on ACM SIGOPS European Workshop. Google Scholar
Digital Library
- Lumb, C., Schindler, J., Ganger, G., Nagle, D., and Riedel, E. 2000. Towards higher disk head utilization: extracting free bandwidth from busy disk drives. In Proceedings of the 4th USENIX Conference on Symposium on Operating System Design & Implementation-Volume 4. Google Scholar
Digital Library
- Meisner, D., Gold, B., and Wenisch, T. 2009. Powernap: Eliminating server idle power. ACM SIGPLAN Notices 44, 3, 205--216. Google Scholar
Digital Library
- Moore, R., D’Aoust, J., McDonald, R., and Minor, D. 2007. Disk and tape storage cost models. http://users.sdsc.edu/~mcdonald/content/papers/dt cost.pdf.Google Scholar
- Narayanan, D., Donnelly, A., and Rowstron, A. 2008. Write off-loading: Practical power management for enterprise storage. ACM Trans. Storage 4, 3, 10. Google Scholar
Digital Library
- Ongaro, D., Rumble, S., Stutsman, R., Ousterhout, J., and Rosenblum, M. 2011. Fast crash recovery in ramcloud. In Proceedings of the 23rd ACM Symposium on Operating Systems Principles. 29--41. Google Scholar
Digital Library
- Phanishayee, A., Krevat, E., Vasudevan, V., Andersen, D., Ganger, G., Gibson, G., and Seshan, S. 2008. Measurement and analysis of tcp throughput collapse in cluster-based storage systems. In Proceedings of the 6th USENIX Conference on File and Storage Technologies (FAST). Google Scholar
Digital Library
- Pinheiro, E. and Bianchini, R. 2004. Energy conservation techniques for disk array-based servers. In Proceedings of the 18th Annual International Conference on Supercomputing (ICS). 68--78. Google Scholar
Digital Library
- Pinheiro, E., Bianchini, R., and Dubnicki, C. 2006. Exploiting redundancy to conserve energy in storage systems. ACM SIGMETRICS Perf. Eval. Rev. 34, 1, 15--26. Google Scholar
Digital Library
- Plank, J. 2005. Erasure codes for storage applications. In Proceedings of 4th USENIX Conference on File and Storage Technologies (FAST)--Tutorial slides.Google Scholar
- Plank, J. et al. 1997. A tutorial on Reed-Solomon coding for fault-tolerance in raid-like systems. Softw. Pract. Exper. 27, 9, 995--1012. Google Scholar
Digital Library
- Plank, J., Luo, J., Schuman, C., Xu, L., and Wilcox-O’Hearn, Z. 2009. A performance evaluation and examination of open-source erasure coding libraries for storage. In Proccedings of the 7th Conference on File and Storage Technologies (FAST). 253--265. Google Scholar
Digital Library
- Rao, K., Hafner, J., and Golding, R. 2011. Reliability for networked storage nodes. IEEE Trans. Dependable Sec. Comput. 8, 3, 404--418. Google Scholar
Digital Library
- Reed, I. and Solomon, G. 1960. Polynomial codes over certain finite fields. J. Soc. Indus. Appl. Math. 8, 2, 300--304.Google Scholar
Cross Ref
- Samsung. 2008. Data sheet of Samsung ddr2 sdram. http://www.samsung.com/.Google Scholar
- Seagate. 2011. Data sheet of seagate disk drive. http://www.seagate.com/docs/pdf/datasheet/.Google Scholar
- Storer, M., Greenan, K., Miller, E., and Voruganti, K. 2008. Pergamum: Replacing tape with energy efficient, reliable, disk-based archival storage. In Proceedings of the 6th USENIX Conference on File and Storage Technologies. Google Scholar
Digital Library
- Tsirogiannis, D., Harizopoulos, S., and Shah, M. 2010. Analyzing the energy efficiency of a database server. In Proceedings of the International Conference on Management of Data. 231--242. Google Scholar
Digital Library
- Wang, J., Zhu, H., and Li, D. 2007. eRAID: Conserving energy in conventional disk-based raid system. IEEE Trans. Comput., 359--374. Google Scholar
Digital Library
- Weatherspoon, H. and Kubiatowicz, J. 2002. Erasure coding vs. replication: A quantitative comparison. In Peer-to-Peer Systems, 328--337. Google Scholar
Digital Library
- Weddle, C., Oldham, M., Qian, J., Wang, A., Reiher, P., and Kuenning, G. 2007. Paraid: A gear-shifting power-aware raid. In Proceedings of the 5th USENIX Conference on File and Storage Technologies (FAST). Google Scholar
Digital Library
- Wilcox-O’Hearn, Z. 2011. Zfec 1.4.2. open source code distribution. http://pypi.python.org/pypi/zfec.Google Scholar
- Xin, Q., Miller, E., Schwarz, T., Long, D., Brandt, S., and Litwin, W. 2003. Reliability mechanisms for very large storage systems. In Proceedings of the 20th IEEE/11th NASA Goddard Conference on Mass Storage Systems and Technologies (MSST). 146--156. Google Scholar
Digital Library
- Yang, L., Li, X., and Zhang, X. 2011. Research on energy consumption of general storage network system. Comput. Eng. (China) 37, 18, 53--58.Google Scholar
- Yao, X. and Wang, J. 2006. Rimac: A novel redundancy-based hierarchical cache architecture for energy efficient, high performance storage systems. ACM SIGOPS Oper. Syst. Rev. 40, 4, 249--262. Google Scholar
Digital Library
- Zhang, Z., Deshpande, A., Ma, X., Thereska, E., and Narayanan, D. 2010. Does erasure coding have a role to play in my data center? Tech. rep. MSR-TR-2010-52, Microsoft.Google Scholar
- Zhu, Q., David, F., Devaraj, C., Li, Z., Zhou, Y., and Cao, P. 2004. Reducing energy consumption of disk storage using power-aware cache management. IEE Proc. Softw., 118--118. Google Scholar
Digital Library
- Zhu, Q., Chen, Z., Tan, L., Zhou, Y., Keeton, K., and Wilkes, J. 2005. Hibernator: Helping disk arrays sleep through the winter. In Proceedings of the 20th ACM Symposium on Operating Systems Principles. 177--190. Google Scholar
Digital Library
- Zyhd. 2010. Zh-101 portable electric power fault recorder and analyzer. http://www.zyhd.com.cn/cN/Bs Product.asp.Google Scholar
Index Terms
Exploiting Redundancies and Deferred Writes to Conserve Energy in Erasure-Coded Storage Clusters
Recommendations
Exploiting In-Memory and On-Disk Redundancy to Conserve Energy in Storage Systems
Today's storage system places an imperative demand on energy efficiency. Storage system often places disks into standby mode by stopping them from spinning to conserve energy when load is not high. The major obstacle of this method is by introducing a ...
Data Delta Based Hybrid Writes for Erasure-Coded Storage Systems
Network and Parallel ComputingAbstractErasure coding is widely used in storage systems since it can offer higher reliability at lower redundancy than data replication. However, erasure-coded storage systems have to perform a partial write to an entire erasure coding group for a small ...
Exploiting redundancy to conserve energy in storage systems
Performance evaluation reviewThis paper makes two main contributions. First, it introduces Diverted Accesses, a technique that leverages the redundancy in storage systems to conserve disk energy. Second, it evaluates the previous (redundancy-oblivious) energy conservation ...








Comments