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International Conference on Advanced Machine Learning Technologies and Applications

AMLTA 2021: Advanced Machine Learning Technologies and Applications pp 593–601Cite as

Towards Improvements on Multi-tenant RDBMS Migration in the Cloud Environment

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1339))

Abstract

In a multi-tenant environment, the companies referred to as tenants share a common application and Relational Database Management System (RDBMS) instances to store their data. However, with the rapid adoption of multi-tenant databases, the cloud provider faces two challenges: Tenants have irregular workload patterns. Also, tenants require a strict guarantee of their rental services’ quality and performance, known as a Service Level Agreement (SLA). In this research, a Multi-Tenant Database Management System (MT DBMS) is presented. A multi-tenant migration algorithm called MT-M is presented, which migrates the violated tenants on an elastic cluster of machines to mitigate the SLA Violations. Experiment results show that the proposed MT-M algorithm is ideal for the migration of the violated multi-tenant databases, reducing SLA violations’ total number compared to the previous migration algorithms.

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Author information

Authors and Affiliations

  1. Faculty of Computer and Information Sciences, Ain Shams University, Cairo, Egypt

    Ahmed E. Abdel Raouf, Alshaimaa Abo-alian & Nagwa L. Badr

Authors
  1. Ahmed E. Abdel Raouf
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  2. Alshaimaa Abo-alian
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  3. Nagwa L. Badr
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Corresponding author

Correspondence to Ahmed E. Abdel Raouf .

Editor information

Editors and Affiliations

  1. Information Technology Department, Cairo University, Computer and Information Faculty, Giza, Egypt

    Aboul-Ella Hassanien

  2. College of Information Science and Engineering, Fujian University of Technology, Fuzhou, Fujian, China

    Kuo-Chi Chang

  3. International Center for Informatics Research, Beijing Jaiotong University, Beijing, China

    Tang Mincong

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© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG

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Raouf, A.E.A., Abo-alian, A., Badr, N.L. (2021). Towards Improvements on Multi-tenant RDBMS Migration in the Cloud Environment. In: Hassanien, AE., Chang, KC., Mincong, T. (eds) Advanced Machine Learning Technologies and Applications. AMLTA 2021. Advances in Intelligent Systems and Computing, vol 1339. Springer, Cham. https://doi.org/10.1007/978-3-030-69717-4_56

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