Comparative Performance Analysis of Load Balancing Techniques in Cloud Computing

doi:10.23940/ijpe.25.07.p6.401410

Abstract

Abstract: Despite widespread use of cloud computing, one of its main challenges is to maintain efficient load balancing and resource allocation. Numerous well-established load balancing techniques have been implemented to optimize task scheduling. The research objectives are equitable resource distribution, overloading prevention, and response time reduction in cloud computing response delays. This study has successfully achieved a comparative performance analysis of four load balancing algorithms — Random, EMPBT-LB, Throttled, and a Proposed Load Balancing (LB) algorithm — evaluated based on their response time performance. The study emphasizes load balancing, where incoming user jobs must be distributed among several virtual machines (VMs) located across different data centers (DCs). The Proposed LB algorithm demonstrates significant improvements over conventional methods by employing a hybrid decision-making approach that incorporates previous processing data, adaptive randomness, and current workload status. The simulation results in the proposed approach (a) achieving the lowest average response time (b) eliminating maximum processing delays, and (c) maintaining high consistency under varying workloads.

Key words: load balancing, virtual machine, data center, random load balancing algorithm, enhanced minimum processing balanced throttling load balancing algorithm, throttled load balancing algorithm

Sunaina Mehta and Sushil Bhardwaj. Comparative Performance Analysis of Load Balancing Techniques in Cloud Computing [J]. Int J Performability Eng, 2025, 21(7): 401-410.

Add to citation manager EndNote|Reference Manager|ProCite|BibTeX|RefWorks

References

[1] Afzal S., andKavitha G., 2019. Load balancing in cloud computing-A hierarchical taxonomical classification. Journal of Cloud Computing,8(1), pp. 1-24.
[2] Roy S., Hossain D.M.A., Sen S.K., Hossain N., andAl Asif M.R., 2019. Measuring the performance on load balancing algorithms.Global J. Comput. Sci. Technol, 19, pp. 41-49.
[3] Panuganti H.R., andSubramanian R., 2024. Enhanced throttled load balancing for virtual machine allocation in multiple data centers. Scalable Computing: Practice and Experience,25(5), pp. 3453-3467.
[4] Hamdani M., Aklouf Y., andChaalal H., 2020. A comparative study on load balancing algorithms in cloud environment. InProceedings of the 10th International Conference on Information Systems and Technologies, pp. 1-4.
[5] Singh A., andKumar R., 2020. Performance evaluation of load balancing algorithms using cloud analyst. In2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence), pp. 156-162.
[6] Kumar P., andKumar R., 2019. Issues and challenges of load balancing techniques in cloud computing: A survey. ACM Computing Surveys (CSUR),51(6), pp. 1-35.
[7] Raghav Y.Y., andVyas V., 2019. A comparative analysis of different load balancing algorithms on different parameters in cloud computing. In2019 3rd International Conference on Recent Developments in Control, Automation & Power Engineering (RDCAPE), pp. 628-634.
[8] Shafiq D.A., Jhanjhi N.Z., Abdullah A., andAlzain M.A., 2021. A load balancing algorithm for the data centers to optimize cloud computing applications.IEEE Access, 9, pp. 41731-41744.
[9] Wang L., Fang W., andDu Y., 2024. Load balancing strategies in heterogeneous environments. Journal of Computer Technology and Applied Mathematics,1(2), pp. 10-18.
[10] Gupta S., Dixit N., andYadav P., 2018. An advanced throttled (ATH) algorithm and its performance analysis with different variants of cloud computing load balancing algorithm. InInternational Conference on Communication, Networks and Computing, pp. 385-399.
[11] Shetty S.M., andShetty S., 2024. Analysis of load balancing in cloud data centers. Journal of Ambient Intelligence and Humanized Computing,15(1), pp. 973-981.
[12] Tripathy J., Das M.N., Panigrahi A., Pati A., Sahoo G., andDash M., 2024. Empirical study on the dynamic load balancing approach in cloud computing. In2024 International Conference on Advancements in Smart, Secure and Intelligent Computing (ASSIC), pp. 1-5.
[13] Elnagar N.G., Elkabbany G.F., Al-Awamry A.A., andAbdelhalim M.B., 2022. Simulation and performance assessment of a modified throttled load balancing algorithm in cloud computing environment. International Journal of Electrical & Computer Engineering (2088-8708),12(2).
[14] Phi N.X., andHung T.C., 2017. Load balancing algorithm to improve response time on cloud computing. International Journal on Cloud Computing: Services and Architecture,7(6), pp. 1-12.