Computer Science ›› 2014, Vol. 41 ›› Issue (10): 154-159.doi: 10.11896/j.issn.1002-137X.2014.10.035

Previous Articles     Next Articles

Minimum-cost Based Data Replication Strategy in Cloud Computing Environment

WU Xiu-guo   

  • Online:2018-11-14 Published:2018-11-14

Abstract: Data replica management is an important component in cloud storage system,which is important for improving the system reliability and high performance.In general,if the number of replicas increase,the transfer cost will be declined because of the data can transfer more effectively;but the storage cost is becoming large because of the existence of additional replicas.Aimed to reduce the cost of data management,this paper proposed a minimum-cost based data replication strategy in balancing storage cost and transfer cost,including the data management cost model,the necessity of adding data replica and an approximate algorithm that can automatically decide the number and their store places.Both the theoretical analysis and simulations conducted on general (random) data sets as well as specific real world applications with Amazon’s cost model show that the minimum-cost replica strategy is close to or even the same as the minimum cost benchmark and the efficiency is very high for practical runtime utilization in the cloud.On the other side,this research can promote the enterprise (user) actively using cloud computing platform and the harmonious development of cloud computing environment.

Key words: Cloud computing,Replication management,Minimum-cost

[1] 王意洁,孙伟东,周松,等.云计算环境下的分布存储关键技术[J].软件学报,2012,3(4):926-986
[2] 张亚勤.未来计算在“云-端”.http://blog.sina.com.cn/s/blog_596ccc870100aps1.html
[3] Furht B,Escalante A.Handbook of Cloud Computing[M].Springer Science Business Media,LLC 2010
[4] Wang L,Luo J,Shen J,et al.Cost and time aware ant colony algorithm for data replica in alpha magnetic spectrometer experiment[C]∥2013 IEEE International Congress on Big Data (BigData Congress).IEEE,2013:247-254
[5] Dong F,Luo J,Song A,et al.An effective data aggregationbased adaptive long term CPU load prediction mechanism on computational grid[J].Future Generation Computer Systems,2012,28(7):1030-1044
[6] Moore R,Prince TA,Ellisman M.Data-Intensive computing and digital libraries[J].Communications of the ACM,1998,1(11):56-62
[7] Bell W H,Cameron D G,Carvajal-Schiaffino R,et al.Evaluation of an economy-based file replication strategy for a data grid[C]∥ Proceedings CCGrid 2003 3rd IEEE/ACM International Symposium on Cluster Computing and the Grid,2003.IEEE,2003:661-668
[8] Ghemawat S,Gobioff H,Leung S T.The Google file system[J].ACM SIGOPS Operating Systems Review,ACM,2003,37(5):29-43
[9] Shvachko K,Kuang H,Radia S,et al.The hadoop distributed file system,Mass Storage Systems and Technologies (MSST)[C]∥2010 IEEE 26th Symposium on.IEEE,2010:1-10
[10] 侯孟书,王晓斌,卢显良,等.一种新的动态副本管理机制[J].计算机科学,2006,3(9):50-51
[11] Foster R K.Identifying Dynamic Replication Strategies for aHigh Performance Data Grid[C]∥Proceeding of the Second International workshop on Grid Computing.Denver,November 2003:75-86
[12] 李静,陈蜀宇,吴长泽.一种基于安全的网格数据副本策略模型[J].计算机应用,2006,6(10):2282-2284
[13] Yuan Dong,Yang Yun,Liu Xiao,et al.A Highly Practical Approach toward Achieving Minimum Data Sets Storage Cost in the Cloud[J].IEEE Transactions on Parallel and Distributed Systems,2013,24(6):1234-1244
[14] S Shao-zhong,K Fan-Sen,W Li-fang.Application of Baumol-Wolfe method on planning location selecting of automotive components manufacturing distribution center,Transportation,Mechanical,and Electrical Engineering (TMEE)[C]∥2011 International Conference on.IEEE,2011:132-136
[15] Winter P.Steiner problem in networks:a survey[J].Networks,1987,17(2):129-167
[16] 李镇坚,朱洪.一种点边带权最小生成树的近似算法[J].计算机应用与软件,2008,25(1):12-13
[17] Yang Y,Liu K,Chen J,et al.An algorithm in SwinDeW-C for scheduling transaction-intensive cost-constrained cloud workflows[C]∥IEEE Fourth International Conference on e-Science.IEEE,2008:374-375

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!