OERD - On Demand and Efficient Replication Dereplication

  • Vardhan Manu
  • Gupta Paras
  • Kushwaha Dharmender Singh
Part of the Advances in Intelligent Systems and Computing book series (volume 167)


For many years, file replication and dereplication in distributed computing environment has been researched to enhance and optimize the scalability of the entire system. Although numerous work have been proposed on the issues of file replication, a comprehensive approach still misses out on various fronts. An effort has been made in the present work to propose a reliable and comprehensive file replication and memory aware dereplication mechanism for a trusted private cloud, based on the file threshold. The proposed approach introduces a File Replication Server (FRS) that is responsible for replicating the file on peer FRS, when the file threshold limit is reached. The proposed approach handles file replication, dereplication, access and performance transparency to the system, thereby ensuring the replication and dereplication decisions about the files in a seamless and efficient manner. The approach is simulated on JAVA platform. A comparative study of the proposed approach with the Request Reply Acknowledgement (RRA) and Request Reply (RR) protocol is presented, showing the significant reduction by 37.5% to 58%, in terms of total number of messages exchanged for file replication.


Replication Logical resource (LR) Service Private cloud IaaS 


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  1. 1.
    Hurley, R.T., Yeap, S.A.: File migration and file replication: a symbiotic relationship. IEEE Trans. on Parallel and Distributed Systems 7, 578–586 (1996)CrossRefGoogle Scholar
  2. 2.
    Mei, A., Mancini, L.V., Jajodia, S.: Secure Dynamic Fragment and Replica Allocation in Large-Scale Distributed File System. IEEE Trans. on Parallel and Distributed Systems 14(9), 885–896 (2003)CrossRefGoogle Scholar
  3. 3.
    Hac, A.: A Distributed Algorithm for Performance Improvement Through File Replication, File Migration, and Process Migration. IEEE Trans. on Software Engg. 15(2), 1459–1470 (1989)MathSciNetCrossRefGoogle Scholar
  4. 4.
    Xiong, K., Perros, H.: Service Performance and Analysis in Cloud Computing. In: World Conference on Services-I, pp. 693–700 (2009)Google Scholar
  5. 5.
    Xu, P., Zheng, W., Wu, Y., Huang, X., Xu, C.: Enabling cloud storage to support traditional applications. In: 5th Annual China Grid Conference, pp. 167–172 (2010)Google Scholar
  6. 6.
    Tsai, W.-T., Zhong, P., Elston, J., Bai, X., Chen, Y.: Service Replication with Map Reduce in Clouds. In: 10th International Symp. on Autonomous Decentralized Systems (ISADS), pp. 381–388 (2011)Google Scholar
  7. 7.
    Sato, H., Matsuoka, S., Endo, T.: File Clustering Based Replication Algorithm in a Grid Environment. In: 9th IEEE/ACM International Symposium on Cluster Computing and the Grid, pp. 204–211 (2009)Google Scholar
  8. 8.
    Panagos, E., Delis, A.: Selective Replication for Content Management Environments. IEEE Journal on Internet Computing 9(3), 45–51 (2005)CrossRefGoogle Scholar
  9. 9.
    Cheng, H.Y., King, C.T.: File Replication for Enhancing the Availability of Parallel I/O Systems on Clusters. In: 1st IEEE Computer Society International Workshop on Cluster Computing, pp. 137–144 (1999)Google Scholar
  10. 10.
    Cabri, G., Corradi, A., Zambonelli, F.: Experience of Adaptive Replication in Distributed File Systems. In: IEEE Proc. of 22nd EUROMICRO Conf. on Beyond 2000: Hardware and Software Design Strategies, pp. 459–466 (1996)Google Scholar
  11. 11.
    Walters, J.P., Chaudhary, V.: Replication-Based Fault Tolerance for MPI Application. IEEE Trans. on Parallel and Distributed Systems 20(7), 997–1010 (2009)CrossRefGoogle Scholar
  12. 12.
    Cloud computing - A premier The Internet protocol Journal 12(3) , (accessed on October 22, 2011)
  13. 13.
    Identifying Applications for Public and Private Clouds, Tom Nolle, Search- cloudcomputing,,289483,sid201_gci1358701,00.html?track=NL-1329&ad=710605&asrc=EM_NLT_7835341&uid=8788654 (accessed on October 22, 2011)
  14. 14.
    Cloud Security Alliance (CSA) (accessed on October 22, 2011)
  15. 15.
    Zheng, L., Hu, Y., Yang, C.: Design and Research on Private Cloud Computing Architecture to Support Smart Grid. In: International Conf. on Intelligent Human-Machine Systems and Cybernetics (IHMSC), August 26-27, pp. 159–161 (2011)Google Scholar
  16. 16.
    Spector, A.Z.: Performing remote operation efficiently on a local computer Network. Communications of the ACM 25(4), 246–259 (1982)MathSciNetCrossRefGoogle Scholar
  17. 17.
    Venkatasubramanian, N., Talcott, C.L.: A Reflective Framework for Providing Safe QoS-enabled Customizable Middleware. In: Workshop on Reflective Middleware, RM 2000 (2000)Google Scholar
  18. 18.
    Chou, C.-F., Golubchik, L., Lui, J.C.S.: Striping doesn’t scale: how to achieve scalability for continuous media servers with replication. In: 20th International Conference on Distributed Computing Systems, pp. 64–71 (2000)Google Scholar
  19. 19.
    Venkatasubramanian, N., Deshpande, M., Mohapatra, S., Gutierrez-Nolasco, S., Wickramasuriya, J.: Design and implementation of a composable reflective middleware framework. In: 21st International Conference on Distributed Computing Systems, pp. 644–653 (April 2001)Google Scholar

Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2012

Authors and Affiliations

  • Vardhan Manu
    • 1
  • Gupta Paras
    • 1
  • Kushwaha Dharmender Singh
    • 1
  1. 1.Computer Science and Engineering DepartmentMNNIT AllahabadAllahabadIndia

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