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@article{202465,
        author = {Pushkar Bati and Mruthunjaya S and Prajwal Gowda H R and Prem and Mithun B N and Krushitha Shetty},
        title = {Intelligent Load Balancing in Web Servers: A Review of Emerging Algorithms and Architecture},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {12},
        pages = {8526-8531},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=202465},
        abstract = {The swift expansion of web services and internet usage has posed considerable challenges in maintaining optimal server performance, particularly in data centers, necessitating the use of load balancing as a crucial technique for distributing workloads among multiple servers to ensure effective resource usage, scalability, and reliability. This examination investigates different load-balancing techniques, including Round-Robin, Least Connections, and Weighted Least Connections, as well as more sophisticated methods like Dynamic Feedback Mechanisms and Reordering-Robust Load Balancing, focusing on enhancing response times, optimizing resource distribution, and improving fault tolerance in both traditional and cloud-based settings. Furthermore, developments in distributed caching, container orchestration, and adaptable server configurations are analyzed to address the requirements of contemporary applications, while machine learning-based strategies such as Dynamic Weighted Polling and Proximity-Based Load Balancing are highlighted for their flexibility and capability to manage high traffic and intricate workloads, ultimately enhancing server efficiency, minimizing latency, and providing a smooth user experience even during peak usage times.},
        keywords = {Load Balancing, web servers, dynamic feedback, resource utilization, cloud computing},
        month = {May},
        }