Online Database Load Balancer to Collaborating With Existing Database

Authors

  • Chavan M Dept. of Computer Engineering, Bharati Vidyapeeth College of Engineering for Women, Pune, India
  • Pawar S Dept. of Computer Engineering, Bharati Vidyapeeth College of Engineering for Women, Pune, India
  • Shaikh S Dept. of Computer Engineering, Bharati Vidyapeeth College of Engineering for Women, Pune, India
  • Wadagave P Dept. of Computer Engineering, Bharati Vidyapeeth College of Engineering for Women, Pune, India
  • Tambat D Dept. of Computer Engineering, Bharati Vidyapeeth College of Engineering for Women, Pune, India

DOI:

https://doi.org/10.26438/ijcse/v6i5.1142146

Keywords:

Auto scalability, Cloud computing,, load balancer, Multi tenancy, Snapshot, Zero downtime

Abstract

According to literature meaning of Cloud Computing is distributed computing, storing, sharing, and accessing data over the internet. Cloud is the platform which provides numerous type of resources where the end user may use the resource for developing own software and even their own cloud and even include a new resource to the existing once. The biggest issue for a cloud datacentre is to tackle with billions of request coming dynamically from the end users to handle their database in efficient and effective manner. To achieve this goal, various load balancing approaches have been proposed in past years. Database load balancing strategies aim at achieving high software developer satisfaction by producing service like auto scale of their data in database, zero-downtime, multiple database choices, multi tenancy support. Load balancing in this environment means equal distribution of workload across instances. End users needs ample space to store their database data to decrease the maintenance cost and buying cost of servers and area required to assemble them this paper focus on the balancing the data in database. This paper, focus on database based load balancing which works well in cloud environment, considers resources specific demands of the tasks and reduces overflow of data overhead by dividing the data on running instances.

References

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[3] Mahajan, K., & Dahiya, D., “A Cloud Based Deployment Framework For Load Balancing Policies” IEEE seventh International Conference on Contemporary Computing, pp. 565-570, August 2014.

[4] Sharma, S., Singh, S., & Sharma, M. “Performance Analysis Of Load Balancing Algorithms” World Academy of Science, Engineering and Technology, 38, pp. 269-272, 2008.

[5] Rahman, M., Iqbal, S., & Gao, J., “Load Balancer as a Service in Cloud Computing”, IEEE 8th

[6] Nuaimi, K. A., Mohamed, N., Nuaimi, M. A., & Al-Jaroodi, J., “A Survey of Load Balancing in Cloud Computing: Challenges and Algorithms” IEEE second symposium on Network Cloud Computing, pp.137-142,December2012.

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Published

2025-11-13
CITATION
DOI: 10.26438/ijcse/v6i5.1142146
Published: 2025-11-13

How to Cite

[1]
M. Chavan, S. Pawar, S. Shaikh, P. Wadagave, and D. Tambat, “Online Database Load Balancer to Collaborating With Existing Database”, Int. J. Comp. Sci. Eng., vol. 6, no. 5, pp. 1142–1149, Nov. 2025.

Issue

Vol. 6 No. 5 (2018): IJCSE May Edition

Section

Review Article

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