Dynamic Load Balancing Mechanisms for Scalable Cloud Computing Architectures

Authors

  • Muhammadu Sathik Raja Professor & Head at Sengunthar Engineering College (Autonomous), Computer Science, Tiruchengode, India. Author

DOI:

https://doi.org/10.63282/3050-9246.IJETCSIT-V6I1P105

Keywords:

Cloud computing, Dynamic load balancing, Resource optimization, Server capacity, Workload distribution

Abstract

In the realm of cloud computing, dynamic load balancing is pivotal for optimizing resource utilization and enhancing system performance. This mechanism ensures that workloads are evenly distributed across multiple servers, preventing any single server from becoming a bottleneck. The proposed Enhanced Dynamic Load Balancing Algorithm introduces a non-AI approach that dynamically adjusts load distribution by considering critical factors such as server capacity, workload distribution, and current system load. By employing adaptive threshold modifications, this novel strategy aims to optimize resource allocation without the complexity and overhead associated with traditional AI-based methods. Experimental results indicate that this approach significantly improves response times and overall system stability compared to existing techniques. As cloud environments continue to evolve, effective load balancing mechanisms will be essential in addressing the challenges of scalability and resource management, ultimately leading to enhanced user satisfaction and operational efficiency

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References

[1] EAI Endorsed Transactions on IoT. Dynamic load balancing in IoT environments. Retrieved from https://publications.eai.eu/index.php/IoT/article/down load/5387/2985/10984

[2] International Journal of Science and Research. (2014). Load balancing algorithms: A review. Retrieved from https://www.ijsr.net/archive/v3i7/MDIwMTQxMzM1 .pdf

[3] MDPI. (2023). Dynamic load balancing in cloud computing systems. Processes, 12(3), 519. Retrieved from https://www.mdpi.com/2227-9717/12/3/519

[4] Google Cloud. Choosing the right load balancer. Retrieved from https://cloud.google.com/loadbalancing/docs/choosing-load-balancer

[5] GeeksforGeeks. Static vs. dynamic load balancing. Retrieved from https://www.geeksforgeeks.org/staticvs-dynamic-load-balancing/

[6] ResearchGate. (2023). Dynamic load balancing in cloud computing: A review and a novel approach. Retrieved from https://www.researchgate.net/publication/378922098 _Dynamic_Load_Balancing_in_Cloud_Computing_ A_Review_and_a_Novel_Approach

[7] IEEE Xplore. (2017). Techniques for dynamic load balancing in distributed systems. Retrieved from https://ieeexplore.ieee.org/document/8076760/

[8] GeeksforGeeks. Load balancing in cloud computing. Retrieved from https://www.geeksforgeeks.org/loadbalancing-in-cloud-computing/

[9] MDPI. (2023). Processes in load balancing for distributed computing systems. Applied Sciences, 13(3), 1586. Retrieved from https://www.mdpi.com/2076-3417/13/3/1586

[10] Techtarget. What are the different types of cloud load balancing? Retrieved from https://www.techtarget.com/searchcloudcomputing/an swer/What-are-the-different-types-of-cloud-loadbalancing

[11] AWS. What is load balancing? Retrieved from https://aws.amazon.com/what-is/loadbalancing/?nc1=h_ls

[12] Cloudflare. Types of load balancing algorithms. Retrieved from https://www.cloudflare.com/learning/performance/typ es-of-load-balancing-algorithms/

[13] JETIR. Load balancing algorithms and their applications. Retrieved from https://www.jetir.org/papers/JETIRAR06009.pdf

[14] Suman, Chintala (2024). Evolving BI Architectures: Integrating Big Data for Smarter Decision-Making. American Journal of Engineering, Mechanics and Architecture, 2 (8). pp. 72-79. ISSN 2993-2637

[15] International Journal of Advanced Computer Science and Applications. (2023). Experimental models for efficient load balancing. Retrieved from https://thesai.org/Publications/ViewPaper?Volume=1 3&Issue=3&Code=IJACSA&SerialNo=16

[16] MDPI. (2020). Performance evaluation of load balancing algorithms in IoT environments. Sensors, 20(24), 7342. Retrieved from https://www.mdpi.com/1424-8220/20/24/7342

[17] Chintala, S. and Thiyagarajan, V., “AI-Driven Business Intelligence: Unlocking the Future of Decision-Making,” ESP International Journal of Advancements in ComputationalTechnology, vol. 1, pp. 73-84, 2023.

[18] IEEE Xplore. (2023). Performance evaluation of dynamic load balancing. Retrieved from https://ieeexplore.ieee.org/document/10176241 [19] PLOS ONE. (2023). Load balancing strategies in distributed systems. Retrieved from https://journals.plos.org/plosone/article?id=10.1371% 2Fjournal.pone.0284176

[20] Chintala, Suman. (2024). “Smart BI Systems: The Role of AI in Modern Business”. ESP Journal of Engineering & Technology Advancements, 4(3): 45- 58.

[21] Fardapaper. (2018). Experimental model for load balancing in cloud computing using throttled algorithm. Retrieved from https://fardapaper.ir/mohavaha/uploads/2018/08/Fard apaper-Experimental-Model-for-Load-Balancing-inCloud-Computing-Using-Throttled-Algorithm.pdf

[22] Applied Sciences. (2020). Dynamic load balancing in distributed cloud systems. Retrieved from https://www.mdpi.com/2076-3417/13/3/1586

[23] International Journal of Intelligent Systems and Applications in Engineering. (2023). Performance evaluation of dynamic load balancing algorithms. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/5833

[24] Kushal Walia, 2024. "Scalable AI Models through Cloud Infrastructure" ESP International Journal of Advancements in Computational Technology (ESPIJACT), Volume 2, Issue 2: 1-7.

[25] Sumanth Tatineni, Anirudh Mustyala, 2024. "Leveraging AI for Predictive Upkeep: Optimizing Operational Efficiency" ESP International Journal of Advancements in Computational Technology (ESP-IJACT), Volume 2, Issue 1: 66-79.

[26] Suman Chintala, "Boost Call Center Operations: Google's Speech-to-Text AI Integration," International Journal of Computer Trends and Technology, vol. 72, no. 7, pp.83-86, 2024. Crossref, https://doi.org/10.14445/22312803/IJCTTV72I7P110

[27] Chandrakanth Lekkala 2022. “Automating Infrastructure Management with Terraform: Strategies and Impact on Business Efficiency”, European Journal of Advances in Engineering and Technology, 2022, 9(11): 82-88.

Published

2025-01-28

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Section

Articles

How to Cite

1.
Muhammadu Sathik Raja. Dynamic Load Balancing Mechanisms for Scalable Cloud Computing Architectures. IJETCSIT [Internet]. 2025 Jan. 28 [cited 2025 Apr. 29];6(1):44-51. Available from: https://ijetcsit.org/index.php/ijetcsit/article/view/29

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