Full Text:   <738>

Summary:  <226>

CLC number: TP316.4

On-line Access: 2016-10-08

Received: 2016-04-13

Revision Accepted: 2016-06-03

Crosschecked: 2016-09-20

Cited: 0

Clicked: 1907

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Nan-nan Zhao

http://orcid.org/0000-0002-7219-7856

-   Go to

Article info.
Open peer comments

Frontiers of Information Technology & Electronic Engineering  2016 Vol.17 No.10 P.994-1007

10.1631/FITEE.1601162


A reliable power management scheme for consistent hashing based distributed key value storage systems


Author(s):  Nan-nan Zhao, Ji-guang Wan, Jun Wang, Chang-sheng Xie

Affiliation(s):  Wuhan National Laboratory for Optoelectronics, Wuhan 430074, China; more

Corresponding email(s):   nnzhaocs@hotmail.com, jgwan@mail.hust.edu.cn, jwang@mail.ucf.edu, cs_xie@mail.hust.edu.cn

Key Words:  Consistent hash table (CHT), Replication, Power management, Key value storage system, Reliability


Nan-nan Zhao, Ji-guang Wan, Jun Wang, Chang-sheng Xie. A reliable power management scheme for consistent hashing based distributed key value storage systems[J]. Frontiers of Information Technology & Electronic Engineering, 2016, 17(10): 994-1007.

@article{title="A reliable power management scheme for consistent hashing based distributed key value storage systems",
author="Nan-nan Zhao, Ji-guang Wan, Jun Wang, Chang-sheng Xie",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="17",
number="10",
pages="994-1007",
year="2016",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.1601162"
}

%0 Journal Article
%T A reliable power management scheme for consistent hashing based distributed key value storage systems
%A Nan-nan Zhao
%A Ji-guang Wan
%A Jun Wang
%A Chang-sheng Xie
%J Frontiers of Information Technology & Electronic Engineering
%V 17
%N 10
%P 994-1007
%@ 2095-9184
%D 2016
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.1601162

TY - JOUR
T1 - A reliable power management scheme for consistent hashing based distributed key value storage systems
A1 - Nan-nan Zhao
A1 - Ji-guang Wan
A1 - Jun Wang
A1 - Chang-sheng Xie
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 17
IS - 10
SP - 994
EP - 1007
%@ 2095-9184
Y1 - 2016
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.1601162


Abstract: 
Distributed key value storage systems are among the most important types of distributed storage systems currently deployed in data centers. Nowadays, enterprise data centers are facing growing pressure in reducing their power consumption. In this paper, we propose GreenCHT, a reliable power management scheme for consistent hashing based distributed key value storage systems. It consists of a multi-tier replication scheme, a reliable distributed log store, and a predictive power mode scheduler (PMS). Instead of randomly placing replicas of each object on a number of nodes in the consistent hash ring, we arrange the replicas of objects on nonoverlapping tiers of nodes in the ring. This allows the system to fall in various power modes by powering down subsets of servers while not violating data availability. The predictive PMS predicts workloads and adapts to load fluctuation. It cooperates with the multi-tier replication strategy to provide power proportionality for the system. To ensure that the reliability of the system is maintained when replicas are powered down, we distribute the writes to standby replicas to active servers, which ensures failure tolerance of the system. GreenCHT is implemented based on Sheepdog, a distributed key value storage system that uses consistent hashing as an underlying distributed hash table. By replaying 12 typical real workload traces collected from Microsoft, the evaluation results show that GreenCHT can provide significant power savings while maintaining a desired performance. We observe that GreenCHT can reduce power consumption by up to 35%–61%.

一种针对基于一致性哈希的键值存储系统的低能耗副本布局策略

概要:分布式键值存储作为最常用的分布式存储系统之一,目前广泛部署在大规模数据中心中。然而,大规模数据中心的高能耗是一个亟待解决的问题。为达到较好节能效果,同时满足数据可用性要求,本文提出一个针对基于一致性哈希的分布式键值存储系统的低能耗副本布局策略——GreenCHT,它包括一个分层副本布局方案、一个可靠的分布式日志和一个预测能耗模式调节器。GreenCHT将副本分布在互不重叠的多个节点层,而非随机放置于哈希环的部分节点。在分层副本布局中,部分节点层可以维持活动状态,其他节点可以被关闭而不影响数据可用性,以达到节能目的。能耗模式调节器(power mode scheduler, PMS)能够预测I/O负载,并根据负载高低波动变化,相应关闭或开启某些节点层。为保证节能状态下的系统可靠性,对于待机副本的写请求,被重新映射到活动的服务器,以保证系统的容错性。通过修改Sheepdog原有的数据分布算法和副本布局策略,GreenCHT被配置在Sheepdog存储集群中。实验中,GreenCHT能够节省35%–61%能耗,同时维持较好性能和可靠性。

关键词:一致性哈希表;副本布局;能源管理;键值存储系统;可靠性

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

[1]Amur, H., Cipar, J., Gupta, V., et al., 2010. Robust and flexible power-proportional storage. Proc. 1st ACM Symp. on Cloud Computing, p.217-228.

[2]Bhagwan, R., Savage, S., Voelker, G.M., 2003. Replication strategies for highly available peer-to-peer storage. In: Future Directions in Distributed Computing. Springer-Verlag, p.153-158.

[3]Box, G.E.P., Jenkins, G., 1990. Time series analysis forecasting and control. In: Wiley Series in Probability and Statistics. Holden-Day, Inc.

[4]Brockwell, P.J., Davis, R.A., 1991. Time series: theory and methods. In: Springer Series in Statistics. Springer-Verlag, New York, NY, USA.

[5]Cisco Systems, 2012. FNV-1. Available from http://www.isthe.com/chongo/tech/comp/fnv/index.html.

[6]Colarelli, D., Grunwald, D., 2002. Massive arrays of idle disks for storage archives. Proc. ACM/IEEE Conf. on Supercomputing, p.1-11.

[7]DeCandia, G., Hastorun, D., Jampani, M., et al., 2007. Dynamo: Amazon's highly available key-value store. Proc. ACM SIGOPS Symp. on Operating Systems Principles, p.205-220.

[8]Goiri, I., Le, K., Haque, M.E., et al., 2011. Greenslot: scheduling energy consumption in green datacenters. Proc. Int. Conf. for High Performance Computing, Networking, Storage and Analysis, p.1-11.

[9]Goiri, I., Le, K., Nguyen, T.D., et al., 2012. GreenHadoop: leveraging green energy in data-processing frameworks. Proc. 7th ACM European Conf. on Computer Systems, p.57-70.

[10]Gorini, S., Quirini, M., Menciassi, A., et al., 2007. PARAID: a Gear-Shifting Power-Aware Raid.

[11]Harnik, D., Naor, D., Segall, I., 2009. Low power mode in cloud storage systems. Proc. Int. Symp. on Parallel and Distributed Processing Systems, p.1-8.

[12]Karger, D., Lehman, E., Leighton, T., et al., 1997. Consistent hashing and random trees: distributed caching protocols for relieving hot spots on the World Wide Web. Proc. 29th Annual ACM Symp. on Theory of Computing, p.654-663.

[13]Kaushik, R.T., Bhandarkar, M., 2010. GreenHDFS: towards an energy-conserving, storage-efficient, hybrid Hadoop compute cluster. Proc. Int. Conf. on Power Aware Computing and Systems, p.1-9.

[14]Kaushik, R., Cherkasova, L., Campbell, R., et al., 2010. Lightning: self-adaptive, energy-conserving, multi-zoned, commodity green cloud storage system. Proc. 19th ACM Int. Symp. on High Performance Distributed Computing, p.332-335.

[15]Lakshman, A., Malik, P., 2010. Cassandra–-a decentralized structured storage system. ACM SIGOPS Oper. Syst. Rev., 44(2):35-40.

[16]Li, C., Qouneh, A., Li, T., 2012. iSwitch: coordinating and optimizing renewable energy powered node clusters. Proc. 39th Annual Int. Symp. on Computer Architecture, p.512-523.

[17]LinkedIn, 2009. Voldemort Project. Available from http://www.project-voldemort.com/voldemort/.

[18]Microsoft Research Ltd., 2014. MRS Cambridge Traces. Available from http://project-voldemort.com/.

[19]MySQL, 2004. SysBench. Available from http://sysbench.sourceforge.net/.

[20]Narayanan, D., Donnelly, A., Rowstron, A., 2008. Write offloading: practical power management for enterprise storage. ACM Trans. Stor., 4(3):1-10.

[21]NTT Group, 2011. Sheepdog. Available from https://github.com/sheepdog/sheepdog/wiki.

[22]Open Source and Linux Organization, 2007. Blktrace User Guide. Hewlett-Packard Company. Available from { break} http://www.cse.unsw.edu.au/aaronc/iosched/doc/blktrace.html.

[23]Park, H., Park, K., 2001. Parallel algorithms for red-black trees. Theor. Comput. Sci., 262(1-2):415-435.

[24]Pinheiro, E., Bianchini, R., 2004. Energy conservation techniques for disk array-based servers. Proc. 18th Annual Int. Conf. on Supercomputing, p.68-78.

[25]Pinheiro, E., Bianchini, R., Dubnicki, C., 2006. Exploiting redundancy to conserve energy in storage systems. Proc. Joint Int. Conf. on Measurement and Modeling of Computer Systems, p.15-26.

[26]Stoica, I., Morris, R., Karger, D., et al., 2001. Chord: a scalable peer-to-peer lookup service for Internet applications. Proc. Conf. on Applications, Technologies, Architectures, and Protocols for Computer Communications, p.149-160.

[27]Thereska, E., Donnelly, A., Narayanan, D., 2011. Sierra: practical power-proportionality for data center storage. Proc. 6th Conf. on Computer Systems, p.169-182.

[28]Zhu, Q., Chen, Z., Tan, L., et al., 2005. Hibernator: helping disk arrays sleep through the winter. 20th ACM Symp. on Operating Systems Principles, {p.177-190}.

Open peer comments: Debate/Discuss/Question/Opinion

<1>

Please provide your name, email address and a comment





Journal of Zhejiang University-SCIENCE, 38 Zheda Road, Hangzhou 310027, China
Tel: +86-571-87952783; E-mail: cjzhang@zju.edu.cn
Copyright © 2000 - Journal of Zhejiang University-SCIENCE