A Neoteric Geo-Distance Based 2- Replica Placing Algorithms on Cloud Storage System

Authors

  • S. Annal Ezhil Selvi Associate Professor, PG. Department of Computer Science, Bishop Heber College (Affiliated to Bharathidasan University), Trichy, TamilNadu, India- 620017.

Keywords:

Cloud Storage, Data Availability, Data Replication, Edge Computing, Reliability, Storage Cost and 2- Replica Placing.

Abstract

In today's digitalized world, all of us have moved to Cloud technology for cloud services to reduce the burden of maintenance issues and to incur lower storage costs than traditional methods. The main reason for the movement of people to the cloud is, it includes its 24/7 service, reliability in all situations, and suitability for large amounts of data storage. Meet out the requirements of high availability and reliability, it adopts a replication system concept. In replication systems, objects are replicated multiple times, and each copy resides in a different geo- location on a distributed computer. It is vulnerable to threats to the Cloud Storage System (CSS). So, this research seeks to explore the mechanisms to rectify the issues mentioned above. Thus, this research work has proposed an algorithm named as 2-Replica Placing (2RP) algorithm which is used to reduce the storage cost, maintenance cost; and maintenance overheads as well as increase the available storage spaces for the providers. This proposed algorithm is placing the data files on two locations based on Geo-Distance and it is used to store only 2-replications with one original file far away from each other in data centers.  The future direction of the research is to maintain the 2-replica concept forever even during a disaster occurring time.

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References

N. Mansouri, M. M. Javidi, M.M. and B. M. H. Zade, “Hierarchical data replication strategy to improve performance in cloud computing,” Front. Comput. Sci. vol. 15, pp. 152-501, 2021.

V. Hadzhiev, "SWOT Analysis of a Hybrid Model for Structuring, Storing and Processing Distributed Data on the Internet," 2021 13th International Conference on Electrical and Electronics Engineering (ELECO), pp. 585-588, 2021.

S. Kianpisheh, M. Kargahi and N. M. Charkari, "Resource Availability Prediction in Distributed Systems: An Approach for Modeling Non-Stationary Transition Probabilities," in IEEE Transactions on Parallel and Distributed Systems, vol. 28, no. 8, pp. 2357-2372, 1 Aug. 2017.

A. Mohammad H. A. Haque, Z. Daka, “On Reliability Management of Energy-Aware Real-Time Systems Through Task Replication,” IEEE Transactions on Parallel & Distributed Systems, vol. 28, no.3 , pp. 813-825, 2017.

S. Annal Ezhil Selvi and Dr. R. Anbuselvi, “Optimizing the Storage Space and Cost with Reliability Assurance by Replica Reduction on Cloud Storage System”, International Journal of Advanced Research in Computer Science (IJARCS),ISSN: 2394-3785,Vol. 8, No. 8, pp. 327-333,2017 (ICI).

Y. Mansouri, A. N. Toosi and R. Buyya “Cost Optimization for Dynamic Replication and Migration of Data in Cloud Data Centers,” IEEE Transactions on Cloud Computing, Vol. pp, No. 99, 2017.

A. Aral and T. Ovatman, "A Decentralized Replica Placement Algorithm for Edge Computing," in IEEE Transactions on Network and Service Management, vol. 15, no. 2, pp. 516-529, June 2018.

C. Liu, "A novel replica placement algorithm for minimising communication cost in distributed storage platform," International Journal of Networking and Virtual Organisations, Inderscience Enterprises Ltd, vol. 22(2), pages 147-161, 2020.

Z. Huang, J. Chen, Y. Lin, P. You, and Y. Peng, “Minimizing data redundancy for high reliable cloud storage systems,” Computer Networks, 81, 164-177, 2015.

W. Li, Y. Yang, and D. Yuan, “Ensuring cloud data reliability with minimum replication by proactive replica checking,” IEEE Transactions on Computers, vol. 65, no.5, 1494-1506, 2015.

A. Lazeb, R. Mokadem, and G. Belalem, “Towards a new data replication management in cloud systems,” International Journal of Strategic Information Technology and Applications (IJSITA), 10(2), 1-20, 2019.

D. Gupta, D and D. Singh, “User preference based page ranking algorithm. In 2016 International Conference on Computing, Communication and Automation (ICCCA) (pp. 166-171), April 2016.

S. Selvi, S and R. Anbuselvi, “Popularity (Hit Rate) Based Replica Creation for Enhancing the Availability in Cloud Storage,” International Journal of Intelligent Engineering & Systems, 11(2), 2018.

N. K. Gill, and S. Singh, “Dynamic cost-aware re-replication and rebalancing strategy in cloud system,” In Proceedings of the 3rd International Conference on Frontiers of Intelligent Computing: Theory and Applications, Vol. 2 (pp. 39-47). Springer International Publishing, 2015.

C. Li, M. Song, M. Zhang, Y. Luo, “Effective replica management for improving reliability and availability in edge-cloud computing environment,” Journal of Parallel and Distributed Computing, vol. 143, 107-128, 2020.

S. Annal Ezhil Selvi., “Geo-Distance Based 2- Replica Maintaining Algorithm for Ensuring the Reliability forever Even during the Natural Disaster on Cloud Storage System”. International Journal on Recent and Innovation Trends in Computing and Communication, 11(7s), 01–07. 2023.

Thomas Wilson, Andrew Evans, Alejandro Perez, Luis Pérez, Juan Martinez. Machine Learning for Anomaly Detection and Outlier Analysis in Decision Science. Kuwait Journal of Machine Learning, 2(3). Retrieved from http://kuwaitjournals.com/index.php/kjml/article/view/207

Sherje, N. P., Agrawal, S. A., Umbarkar, A. M., Kharche, P. P., & Dhabliya, D. (2021). Machinability study and optimization of CNC drilling process parameters for HSLA steel with coated and uncoated drill bit. Materials Today: Proceedings, doi:10.1016/j.matpr.2020.12.1070

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Published

16.07.2023

How to Cite

Selvi, S. A. E. . (2023). A Neoteric Geo-Distance Based 2- Replica Placing Algorithms on Cloud Storage System. International Journal of Intelligent Systems and Applications in Engineering, 11(3), 769–774. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/3283

Issue

Vol. 11 No. 3 (2023)

Section

Research Article

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