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Hierarchical data replication strategy to improve performance in cloud computing

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Abstract

Cloud computing environment is getting more interesting as a new trend of data management. Data replication has been widely applied to improve data access in distributed systems such as Grid and Cloud. However, due to the finite storage capacity of each site, copies that are useful for future jobs can be wastefully deleted and replaced with less valuable ones. Therefore, it is considerable to have appropriate replication strategy that can dynamically store the replicas while satisfying quality of service (QoS) requirements and storage capacity constraints. In this paper, we present a dynamic replication algorithm, named hierarchical data replication strategy (HDRS). HDRS consists of the replica creation that can adaptively increase replicas based on exponential growth or decay rate, the replica placement according to the access load and labeling technique, and finally the replica replacement based on the value of file in the future. We evaluate different dynamic data replication methods using CloudSim simulation. Experiments demonstrate that HDRS can reduce response time and bandwidth usage compared with other algorithms. It means that the HDRS can determine a popular file and replicates it to the best site. This method avoids useless replications and decreases access latency by balancing the load of sites.

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Authors and Affiliations

  1. Department of Computer Science, Shahid Bahonar University of Kerman, Kerman, 76169-14111, Iran

    Najme Mansouri, Mohammad Masoud Javidi & Behnam Mohammad Hasani Zade

  2. Mahani Mathematical Research Center, Shahid Bahonar University of Kerman, Kerman, 76169-14111, Iran

    Najme Mansouri, Mohammad Masoud Javidi & Behnam Mohammad Hasani Zade

Authors
  1. Najme Mansouri
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  2. Mohammad Masoud Javidi
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  3. Behnam Mohammad Hasani Zade
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Correspondence to Najme Mansouri.

Additional information

Najme Mansouri is currently a faculty of Computer Science at Shahid Bahonar University of Kerman, Iran. She received her PhD in Computer Science from Shahid Bahonar University of Kerman, Iran and MSc in software engineering at Department of Computer Science & Engineering, College of Electrical & Computer Engineering, Shiraz University, Iran. She received her BSc (Honor Student) in Computer Science from Shahid Bahonar University of Kerman, Iran in 2009. She has published more than 40 scientific papers in the field of high-performance, parallel processing, grid and cloud computing, and contributed to more than 20 research and development programs.

Mohammad Masoud Javidi is currently an associate professor of Computer Science in Department of Computer Science, Shahid Bahonar University of Kerman, Iran. His research interests include distributed systems, and cloud computing. He has published more than 50 articles in journals and conferences.

Behnam Mohammad Hasani Zade received MSc degree in computer science from Shahid Bahonar University of Kerman, Kerman, Iran in 2018. His researches interests are in the areas of evolutionary algorithms, swarm intelligence, multi-objective optimization, machine learning and cloud computing.

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Mansouri, N., Javidi, M.M. & Zade, B.M.H. Hierarchical data replication strategy to improve performance in cloud computing. Front. Comput. Sci. 15, 152501 (2021). https://doi.org/10.1007/s11704-019-9099-8

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