A Review of Meta Heuristic Algorithms and ‎Its Evaluation for Load Balancing in Cloud ‎Computing

  • Authors

    • S. Balaji Institute of Computer Science and Information Science, Srinivas University. ‎Mangaluru-574146, Karnataka, India and Department of Information Technology, Al Zahra College for Women, Ghala, Muscat
    • S. Silvia Priscila Department of Computer Science, Bharath Institute of Higher Education and Research, Tamil Nadu 600126, India
    • Praveen B. M Institute of Engineering and Technology, Srinivas University, Mangaluru-574146, Karnataka, India
    https://doi.org/10.14419/bp2nsc52

    Received date: July 18, 2025

    Accepted date: September 7, 2025

    Published date: October 2, 2025

  • Artificial Intelligence; Cloud Computing; Load Balancing; Meta-heuristic Algorithms

  • Abstract

    Cloud computing(CC), which utilizes massively virtualized data centers to deliver quick and affordable computing solutions, has developed ‎into an established industrial standard that is growing quickly. To handle such a massive amount of data effectively, cloud computing mostly ‎relies on automation and dynamic resource management. In cloud computing, load balancing (LB) is a vital technique for maximizing ‎resource utilization and making sure that no resource is used up. Without the requirement for physical infrastructure, cloud ‎LB allows online platforms to adjust their resources in response to traffic demands. In a cloud environment, workload and resource allocation entail determining the best way to divide up work among several servers. For increasingly severe uncertainty problems, traditional LB ‎approaches are simple but ineffective; for this reason, meta-heuristic methods are employed. This algorithm is heuristic and is independent ‎of the complexity of the challenges. Meta-heuristics approaches based on Artificial Intelligence (AI) are employed to analyze real-time data ‎and intelligently distribute workload among servers. This ensures efficient operations by preventing bottlenecks and enabling proactive LB ‎decisions. The review offers a thorough analysis of meta-heuristics techniques based on artificial intelligence (AI) for static and dynamic LB ‎in both homogeneous and heterogeneous cloud systems.

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    Balaji , S. ., Priscila , S. S. ., & M, P. B. . (2025). A Review of Meta Heuristic Algorithms and ‎Its Evaluation for Load Balancing in Cloud ‎Computing. International Journal of Basic and Applied Sciences, 14(6), 12-20. https://doi.org/10.14419/bp2nsc52