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Link to original content: https://unpaywall.org/10.1007/S11227-022-04662-6
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Energy-efficient polyglot persistence database live migration among heterogeneous clouds

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Abstract

Cloud computing is seen as a more promising technology than any other traditional information technology computing paradigm in today’s world. It essentially functions as an on-demand resource provisioning platform that requires no active user participation. The resource provisioning strategies necessitate proper load distribution management across the cloud network, without which the cloud would experience biased workload performance. Today virtualization is the cornerstone of cloud computing, allowing data dissemination and administration via deploying virtual machines. Modern applications contain data that need to be stored into a scheme called polyglot persistence (combining SQL and NoSQL data-stores). However, these services are tailored to specific storage requirements, necessitating aggregating them from several heterogeneous clouds or migrating data from one cloud to another. Data migration can be done offline where the database is independent of the application, or otherwise, the application has to be down for the migration period. This paper developed a middleware in .NET Core facilitating the live migration of persistent polyglot data in heterogeneous clouds. This paper presents the proof of concept for live migration of the database layer of an application hosted on any supported clouds to any implemented cloud’s data-store. Our suggested technique performs better in migration time, energy usage, and throughput aspects as compared with the offline migration scenario. In our experimentation, we found that while migrating data in offline mode from SQL to mongo and vice versa there is a marginal increase of 29% and 11%, respectively, in latency time. This increase is acceptable and tolerable while considering the live data migration scenario.

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Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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Authors and Affiliations

  1. Guru Nanak Dev University, Amritsar, Punjab, India

    Kiranbir Kaur, Salil Bharany & Sandeep Sharma

  2. Computer Science Engineering Department, Lovely Professional University, Jalandhar, Punjab, India

    Sumit Badotra

  3. Electronics and Communication Engineering Department, Maharishi Markandeshwar (Deemed to be University), Mullana, Ambala, Haryana, India

    Karan Aggarwal

  4. Faculty of Information Technology, Graduate School, Duy Tan University, Da Nang, Vietnam

    Anand Nayyar

Authors
  1. Kiranbir Kaur
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  2. Salil Bharany
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  6. Sandeep Sharma
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Correspondence to Karan Aggarwal.

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Kaur, K., Bharany, S., Badotra, S. et al. Energy-efficient polyglot persistence database live migration among heterogeneous clouds. J Supercomput 79, 265–294 (2023). https://doi.org/10.1007/s11227-022-04662-6

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