DM Based Multi-Tenant Framework to Perform Migration in Cloud Environment

Abstract

Amazon Web Services, or AWS, is an easy-to-use, flexible, and reasonably priced cloud platform. Many Amazon Web Services (AWS) customers use RDBMS, or relational database management systems. Deploying and setting up relational database management systems is made easier with Oracle Database on AWS. Relational Database Service (RDS) by Amazon allows users to manage Oracle databases. These challenges are distilled into a Service Level Agreement (SLA) that specifies the standards for the quality of service provided to tenants. In addition, SLA needs to think about how renters' irregular workload patterns can affect the level of assurance. In order to address the issue mentioned before, the recommended strategy involves operating Oracle Database on an Amazon RDS-based Multi-Tenant system and reaping the benefits of it. This TransDB approach facilitates Oracle database deployment and monitoring, as well as efficient framework management in Amazon RDS with enhanced scalability, performance, backup/recovery, availability, and security. Analyzed performance metrics include CPU, memory, and network throughput; resources may be instantly resized; and the network topology is provisioned to ensure increased security. When put up against established strategies like Allocation and the MT-M method, the suggested approach proves to be the superior choice. 

Country : USA

1 Mohammed Sadhik Shaik

  1. Sr. Software Web Developer Engineer, Computer Science, Germania Insurance, Melissa, Texas, USA

IRJIET, Volume 9, Issue 4, April 2025 pp. 75-81

doi.org/10.47001/IRJIET/2025.904010

References

  1. Armbrust M, Fox A, Griffith R, Joseph AD, Katz R, Konwinski A, Lee G, Patterson D, Rabkin A, Stoica I, Zaharia M (2010) A view of cloud computing. Commun ACM 53(4):50–58. [Online]. Available: http://doi.acm.org/10.1145/1721654.1721672.
  2. Khazaei H, Misic J, Misic VB (2012) Performance analysis of cloud computing centers using m/g/m/m+ r queuing systems. Parallel Distrib Syst IEEE Trans on 23(5):936–943.
  3. Fehling C, Leymann F, Retter R, Schupeck W, Arbitter P (2014) Cloud Computing Patterns. Springer, London.
  4. Bauer E, Adams R (2012) Reliability and availability of cloud computing. Wiley, New Jersey.
  5. Ochei LC, Bass J, Petrovski A (2015) Evaluating degrees of multitenancy isolation: A case study of cloud-hosted gsd tools In: 2015 International Conference on Cloud and Autonomic Computing (ICCAC), 101–112. IEEE. https://ieeexplore.ieee.org/abstract/document/7312145/.
  6. Ochei LC, Petrovski A, Bass J (2015) Evaluating degrees of isolation between tenants enabled by multitenancy patterns for cloud-hosted version control systems (vcs). Int J Intell Comput Res 6(3):601–612.
  7. Ochei LC, Bass J, Petrovski A (2016) Implementing the required degree of multitenancy isolation: A case study of cloud-hosted bug tracking system In: 13th IEEE International Conference on Services Computing (SCC 2016). IEEE.
  8. Runeson P, Host M, Rainer A, Regnell B (2012) Case study research in software engineering: Guidelines and examples. Wiley, New Jersey.
  9. Cruzes DS, Dybå T, Runeson P, Höst M (2015) Case studies synthesis: a thematic, cross-case, and narrative synthesis worked example. Empir Softw Eng 20(6):1634–1665.
  10. Cruzes DS, Dybå T (2011) Research synthesis in software engineering: A tertiary study. Inf Softw Technol 53(5):440–455.
  11. Chong F, Carraro G (2006) Architecture strategies for catching the long tail. Technical report, Microsoft. [Online https://msdn.microsoft.com/en-us/library/aa479069.aspx]. Accessed Oct 2018.
  12. Wang ZH, Guo CJ, Gao B, Sun W, Zhang Z, An WH (2008) A study and performance evaluation of the multi-tenant data tier design patterns for service oriented computing In: IEEE International Conference on e-Business Engineering, 94–101. IEEE. https://ieeexplore.ieee.org/abstract/document/4690605/.
  13. Vengurlekar N (2012) Isolation in private database clouds. Oracle Corporation. [Online https://www.oracle.com/technetwork/database/database-cloud/]. Accessed Oct 2018.
  14. Walraven S, De Borger W, Vanbrabant B, Lagaisse B, Van Landuyt D, Joosen W (2015) Adaptive performance isolation middleware for multi-tenant saas In: Utility and Cloud Computing (UCC), 2015 IEEE/ACM 8th International Conference on, 112–121. IEEE. https://ieeexplore.ieee.org/abstract/document/7431402/.
  15. Mietzner R, Unger T, Titze R, Leymann F (2009) Combining different multi-tenancy patterns in service-oriented applications In: Proceedings of the 2009 IEEE International Enterprise Distributed Object Computing Conference (edoc 2009), 131–140. IEEE. https://ieeexplore.ieee.org/abstract/document/5277698/.
  16. Guo CJ, Sun W, Huang Y, Wang ZH, Gao B (2007) A framework for native multi-tenancy application development and management In: Proceedings of the 2007 IEEE International Conference on ECommerce Technology and the IEEE International Conference on Enterprise Computing, E-Commerce, and EServices, 551–558. IEEE. http://doi.ieeecomputersociety.org/10.1109/CEC-EEE.2007.4.
  17. Walraven S, Monheim T, Truyen E, Joosen W (2012) Towards performance isolation in multi-tenant saas applications In: Proceedings of the 7th Workshop on Middleware for Next Generation Internet Computing, 6. ACM.
  18. Krebs R, Wert A, Kounev S (2013) Multi-tenancy performance benchmark for web application platforms In: Web Engineering, 424–438. Springer, Berlin. https://link.springer.com/chapter/10.1007/978-3-642-39200-9_36.