Mohammed Abdul Azeem
T. Ragunathan
ABSTRACT
Replication has been used in cloud storage systems as a way to increase data availability. Existing replication strategies proposed for cloud storage systems allow users to fix the replication factor to replicate data. The problem with this approach is that either the user under estimates or over estimates the replication factor due to which the performance of the cloud storage system is affected. In this paper, we have proposed support-based replication algorithm which decides the replication factor based on the popularity of the file and access frequency of the blocks contained in the file. We have also proposed efficient way of placing the replicas in the cloud storage systems in order to improve the performance. Our analysis on storage and average read access time indicates that the proposed replication algorithm requires less storage space and provides better average read access time in comparison with Hadoop distributed file system.
- Rajkumar, B., Christian V., and Thamarai S. S. 2013. Mastering Cloud Computing. Mc Graw Hill Education, 1st Edition. (2013), 14--15.Google Scholar
- Da-Wei S., Gui-Ra C., Shang G., Li-Zhong J., and Xing-Wei W. 2012. Modeling a Dynamic Data Replication Strategy to Increase System Availability in Cloud Computing Environments, Journal of computer science and technology, (2012), 256--272.Google Scholar
- Qingsong W., Bharadwaj V., Bozhao G., Lingfang Z., Dan F, 2010. CDRM: A Cost-effective Dynamic Replication Management Scheme for Cloud Storage Cluster. IEEE International Conference on Cluster Computing. (2010), 188--196. Google ScholarDigital Library
- Xin S., Jun Z., Qiongxin L., Yushu L. 2009. Dynamic Data Replication on Access Cost in Distributed Systems. (2009), 829--834. Google ScholarDigital Library
- Wenhao L., Yun Y., Dong Yuan. 2011. A Novel Cost-effective Dynamic Data Replication Strategy for Reliability in Cloud Data Centres. Ninth IEEE International Conference on Dependable, Autonomic and Secure Computing. (2011), 496--502. Google ScholarDigital Library
- Frezewd L., Johannes S., Christof F. 2013. Dynamic Replication Technique for Micro-Clouds Based Distributed Storage System. Third IEEE International Conference on Cloud and Green Computing. (2013), 48--53. Google ScholarDigital Library
- ZhenQi W., HaiLong L. 2013. Research of Massive Web Log Data Mining Based on Cloud Computing. International Conference on Computation and Information Science. (2013), 591--594. Google ScholarDigital Library
- Jiawei H., Michelin K. 2007. Data Mining Concepts and Techniques. 2nd Edition, (2007), 23--29.Google Scholar
- Chris X. C., Critina L. A., Roy H. C. 2013. Storage-Efficient Data Replica Number Computation for Multi-Level Priority Data in Distributed Storage Systems. 2013.Google Scholar
- Shravanth O., Qin D., Nasseh T. 2013. Exploring HADOOP as a Platform for Distributed Association Rule Mining, The 5th International Conference on Future Computational Technologies and Applications. (2013), 62--67.Google Scholar
- Zhang T. 2013. Data Replication Placement in Cloud Storage System. International Workshop on Cloud Computing and Information Security (CCIS). (2013), 551--554.Google Scholar
- Vikram P., RadhaKrishna P. 2010. Data Mining. First Edition. Oxford university press. (2010), 25--32.Google Scholar
- Thanasis L., Petros L., Ishfaq A. 2005. Continuous Replica Placement Schemes in Distributed Systems. (2005), 284--292. Google ScholarDigital Library
- Itziar Arrieta-S., Jos'e E., Armend'ariz-I., Joan N. 2012. Classic Replication Techniques on the Cloud. Seventh International Conference on Availability, Reliability and Security. (2012), 268--273. Google ScholarDigital Library
- Huiping P. 2010. Discovery of Interesting Association Rules Based on Web Usage Mining. International Conference on Multimedia Communications. (2010), 272--275. Google ScholarDigital Library
- Zhendong C., Zhongzhi L., You M., Yijing X., Depei Q., Alain R., Ning Z., Gang G. 2012. ERMS: An ElasticReplication Management System for HDFS. International conference on Cluster Computing Workshops. (2012), 32--40. Google ScholarDigital Library
- Manu V., Akhil., Abhinav V., Dharmender S. K. 2012. Demand Based File Replication and Consistency Mechanism. Third International Conference on Computer and Communication Technology. (2012), 335--339. Google ScholarDigital Library
- Ruay-Shiung C., Hui-Ping C., Yun-Ting W. 2008. A Dynamic Weighted Data Replication Strategy in Data Grids. IEEE. (2008), 414--421 Google ScholarDigital Library
- Wenhao L., Yun Y., Jinjun C., Dong Yuan. 2012. A Cost-Effective Mechanism for Cloud Data Reliability Management Based on Proactive Replica Checking. 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing. (2012), 564--571. Google ScholarDigital Library
- Support-based replication algorithm for cloud storage systems
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