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A novel dynamic data replication strategy to improve access efficiency of cloud storage

Author

Listed:
  • Sujaudeen Nannai John

    (SSN College of Engineering)

  • T. T. Mirnalinee

    (SSN College of Engineering)

Abstract

Cloud computing provides on demand services to cloud users, and one among them is storage. Currently, large amount of data gets generated and demand an enormous storage. Users can avail the privilege to store their data remotely and can access them through Internet. Of course, the adoption of cloud lends the kind of storage that the user wants. Since data gets accumulated, the time it takes to store and retrieve the data is very long and difficult. Also, unfortunately the existing method of storage is to be optimized for better performance. The factors that affect the performance of cloud storage are response time, data availability and migration cost. Hence to improve these factors the data can be replicated to multiple locations. The decision on which data to be replicated, number of replicas to be created, where the replica has to be placed, management of the replicated data and the provision of optimal replica to the user are the major challenges involved in dynamic replication. We intend to propose, a novel dynamic data replication strategy with intelligent water drop (IWD) algorithm to address the challenges of replication and for the management of cloud storage. The popularity and size of the data are considered for replication. A swarm intelligence based optimization algorithm named IWD algorithm is used to optimize the process of replication and management of storage in cloud. We have compared our D2R-IWD algorithm with popular optimization techniques such as PSO, GA and found out that our methodology gives better result in terms of access efficiency for several test cases thereby improve the performance of cloud.

Suggested Citation

  • Sujaudeen Nannai John & T. T. Mirnalinee, 2020. "A novel dynamic data replication strategy to improve access efficiency of cloud storage," Information Systems and e-Business Management, Springer, vol. 18(3), pages 405-426, September.
    • Handle: RePEc:spr:infsem:v:18:y:2020:i:3:d:10.1007_s10257-019-00422-x
    DOI: 10.1007/s10257-019-00422-x
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