Analysis of load balancing algorithms in cloud computing

Authors

  • O.I. Shklyar State University "Kyiv Aviation Institute"

DOI:

https://doi.org/10.18372/2073-4751.82.20374

Keywords:

cloud computing, CloudSim, load balancing, simulation, task scheduling algorithms, Honeybee Foraging, Min-Min, ANOVA, virtualization, datacenter

Abstract

This article presents the results of a simulation-based study on the performance of various load balancing algorithms in a cloud service infrastructure using the CloudSim v7.0.0 platform. The simulated environment included one datacenter with 10 hosts, 50 virtual machines, and 200 cloudlet tasks. Seven load balancing algorithms were compared: Round Robin, Throttled Load Balancing, Active Monitoring, Weighted Least Connection, Biased Random Sampling, Min-Min, and Honeybee Foraging. Simulation outcomes were evaluated based on average task completion time, CPU utilization, load variance, and task migration count. Statistical analysis, including ANOVA and pairwise t-tests, revealed significant differences in algorithm efficiency. Based on the findings, further improvement directions for load balancing strategies are proposed, with a focus on adaptive and hybrid approaches.

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Published

2025-08-23

How to Cite

Shklyar, O. (2025). Analysis of load balancing algorithms in cloud computing. Problems of Informatization and Control, 2(82), 102–107. https://doi.org/10.18372/2073-4751.82.20374

Issue

Vol. 2 No. 82 (2025)

Section

Статті

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