Full Text:   <1468>

Summary:  <916>

CLC number: TP393

On-line Access: 2016-03-16

Received: 2015-11-10

Revision Accepted: 2016-02-16

Crosschecked: 2016-11-14

Cited: 0

Clicked: 4060

Citations:  Bibtex RefMan EndNote GB/T7714


Reza Sookhtsaraei


-   Go to

Article info.
Open peer comments

Frontiers of Information Technology & Electronic Engineering  2016 Vol.17 No.12 P.1275-1286


A locality-based replication manager for data cloud

Author(s):  Reza Sookhtsaraei, Javad Artin, Ali Ghorbani, Ahmad Faraahi, Hadi Adineh

Affiliation(s):  1Department of Computer Engineering and Information Technology, Payame Noor University, Tehran, Iran; more

Corresponding email(s):   reza.sookhtsaraei@gmail.com

Key Words:  Data cloud, Replication, Graph, Locality replication manager (LRM)

Reza Sookhtsaraei, Javad Artin, Ali Ghorbani, Ahmad Faraahi, Hadi Adineh. A locality-based replication manager for data cloud[J]. Frontiers of Information Technology & Electronic Engineering, 2016, 17(12): 1275-1286.

@article{title="A locality-based replication manager for data cloud",
author="Reza Sookhtsaraei, Javad Artin, Ali Ghorbani, Ahmad Faraahi, Hadi Adineh",
journal="Frontiers of Information Technology & Electronic Engineering",
publisher="Zhejiang University Press & Springer",

%0 Journal Article
%T A locality-based replication manager for data cloud
%A Reza Sookhtsaraei
%A Javad Artin
%A Ali Ghorbani
%A Ahmad Faraahi
%A Hadi Adineh
%J Frontiers of Information Technology & Electronic Engineering
%V 17
%N 12
%P 1275-1286
%@ 2095-9184
%D 2016
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.1500391

T1 - A locality-based replication manager for data cloud
A1 - Reza Sookhtsaraei
A1 - Javad Artin
A1 - Ali Ghorbani
A1 - Ahmad Faraahi
A1 - Hadi Adineh
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 17
IS - 12
SP - 1275
EP - 1286
%@ 2095-9184
Y1 - 2016
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.1500391

Efficient data management is a key issue for environments distributed on a large scale such as the data cloud. This can be taken into account by replicating the data. The replication of data reduces the time of service and the delay in availability, increases the availability, and optimizes the distribution of load in the system. It is worth mentioning, however, that with the replication of data, the use of resources and energy increases due to the storing of copies of the data. We suggest a replication manager that decreases the cost of using resources, energy, and the delay in the system, and also increases the availability of the system. To reach this aim, the suggested replication manager, called the locality replication manager (LRM), works by using two important algorithms that use the physical adjacency feature of blocks. In addition, a set of simulations are reported to show that LRM can be a suitable option for distributed systems as it uses less energy and resources, optimizes the distribution of load, and has more availability and less delay.

In this paper, authors proposed a locality-based replication manager (LRM) for data cloud. In LRM, authors utilise genetic algorithm to optimise the availability and delay of the system. Simulation results compared to other two representative replication strategies show the performance improvement of the proposed approach.


摘要:有效的数据处理是大规模分布式环境(如云数据)中的一个关键性问题,其中需要考虑到数据的复制。数据复制可以减少服务时间和获取数据所需的时间,增加可用性并优化系统负载分布。然而值得一提的是,数据的同样会增加储存数据所需的资源和能源。我们提出了一种可减少资源、能源消耗,减少系统延迟,并增加系统可用性的复制管理器,称为位置复制管理器(Locality replication manager, LRM)。这一管理器采用的两种重要算法利用了数据块之间的物理邻接特性。对LRM进行的一系列模拟结果显示,LRM消耗了较少的资源和能源,优化了系统负载分布,并增加了系统可用性,减少了系统延迟,因此适用对于分布式系统。


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


[1]Aazami, A., Ghandeharizadeh, S., Helmi, T., 2004. Near optimal number of replicas for continuous media in ad-hoc networks of wireless devices. Proc. 1st Workshop on Multimedia Information Systems.

[2]Amazon, 2008. Amazon Simple Storage Service (Amazon S3). Available from http://aws.amazon.com/s3.

[3]Armbrust, M., Fox, A., Griffith, R., et al., 2009. Above the Clouds: a Berkeley View of Cloud Computing. Technical Report, No. UCB/EECS-2009-28, Department of EECS, California University, Berkeley.

[4]Bonvin, N., Papaioannou, T.G., Aberer, K., 2009. Dynamic cost-efficient replication in data clouds. Proc. 1st Workshop on Automated Control for Datacenters and Clouds, p.49-56.

[5]Buyya, R., Yeo, C.S., Venugopal, S., et al., 2009. Cloud computing and emerging IT platforms: vision, hype, and reality for delivering computing as the fifth utility. Fut. Gener. Comput. Syst., 25(6):599-616.

[6]Chang, R.S., Chang, H.P., 2008. A dynamic data replication strategy using access weights in data grids. J. Supercomput., 45(3):277-295.

[7]Choi, S.C., Youn, H.Y., 2012. Dynamic hybrid replication effectively combining tree and grid topology. J. Supercomput., 59(3):1289-1311.

[8]Creeger, M., 2009. Cloud computing: an overview. ACM Queue, 7(5):2-4.

[9]Dabrowski, C., 2009. Reliability in grid computing systems. Concurr. Comput. Pract. Exp., 21(8):927-959.

[10]Dikaiakos, M.D., Katsaros, D., Mehra, P., et al., 2009. Cloud computing: distributed Internet computing for IT and scientific research. IEEE Internet Comput., 13(5):10-13.

[11]Doğan, A., 2009. A study on performance of dynamic file replication algorithms for real-time file access in data grids. Fut. Gener. Comput. Syst., 25(8):829-839.

[12]Ghemawat, S., Gobioff, H., Leung, S., 2003. The Google file system. Proc. 19th ACM Symp. on Operating Systems Principles, p.29-43.

[13]Hassan, O.A.H., Ramaswamy, L., Miller, J., et al., 2009. Replication in overlay networks: a multi-objective optimization approach. Int. Conf. on Collaborative Computing: Networking, Applications and Worksharing, p.512-528.

[14]Intanagonwiwat, C., Govindan, R., Estrin, D., 2000. Directed diffusion: a scalable and robust communication paradigm for sensor networks. Proc. 6th Annual Int. Conf. on Mobile Computing and Networking, p.56-67.

[15]Lamehamedi, H., Shentu, Z., Szymanski, B., et al., 2003. Simulation of dynamic data replication strategies in data grids. Proc. Int. Parallel and Distributed Processing Symp.

[16]Lei, M., Vrbsky, S.V., Hong, X.Y., 2008. An on-line replication strategy to increase availability in data grids. Fut. Gener. Comput. Syst., 24(2):85-98.

[17]Li, W.H., Yang, Y., Yuan, D., 2011. A novel cost-effective dynamic data replication strategy for reliability in cloud data centres. IEEE 9th Int. Conf. on Dependable, Autonomic and Secure Computing, p.496-502.

[18]Li, W.H., Yang, Y., Chen, J.J., et al., 2012. A cost-effective mechanism for cloud data reliability management based on proactive replica checking. 12th IEEE/ACM Int. Symp. on Cluster, Cloud and Grid Computing, p.564-571.

[19]Nukarapu, D.T., Tang, B., Wang, L.Q., et al., 2011. Data replication in data intensive scientific applications with performance guarantee. IEEE Trans. Parall. Distr. Syst., 22(8):1299-1306.

[20]Qiu, L.L., Padmanabhan, V.N., Voelker, G.M., 2001. On the placement of Web server replicas. Proc. IEEE 20th Annual Joint Conf. of the IEEE Computer and Communications Societies.

[21]Rahman, R.M., Barker, K., Alhajj, R., 2006. Replica placement design with static optimality and dynamic maintainability. Proc. 6th IEEE Int. Symp. on Cluster Computing and the Grid, p.434-437.

[22]Ranganathan, K., Foster, I.T., 2001. Identifying dynamic replication strategies for a high-performance data grid. Int. Workshop on Grid Computing, p.75-86.

[23]Shvachko, K., Hairong, K., Radia, S., et al., 2010. The Hadoop distributed file system. IEEE 26th Symp. on Mass Storage Systems and Technologies, p.1-10.

[24]Tang, B., Das, S.R., Gupta, H., 2008. Benefit-based data caching in ad hoc networks. IEEE Trans. Mob. Comput., 7(3):289-304.

[25]Tang, X., Xu, J., 2005. QoS-aware replica placement for content distribution. IEEE Trans. Parall. Distr. Syst., 16(10):921-932.

[26]Tu, M., Tadayon, T., Xia, Z., et al., 2007. A secure and scalable update protocol for P2P data grids. 10th IEEE High Assurance Systems Engineering Symp., p.423-424.

[27]Wei, Q., Veeravalli, B., Gong, B., et al., 2010. CDRM: a cost-effective dynamic replication management scheme for cloud storage cluster. IEEE Int. Conf. on Cluster Computing, p.188-196.

Open peer comments: Debate/Discuss/Question/Opinion


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