Intelligent and Adaptive Load Balancing in Cloud Environments: A Review
Keywords:
Cloud Computing, Load Balancing, Adaptive Strategies, Intelligent Techniques, Performance OptimizationAbstract
Cloud computing delivers scalable and flexible services, but fluctuating workloads and heterogeneous resources pose significant challenges to efficient performance. Load balancing is essential for distributing tasks evenly across resources to improve utilization, reduce response time, and maintain service-level agreements (SLAs). Traditional methods are often static and limited in adaptability, whereas intelligent and adaptive strategies leverage machine learning, heuristic optimization, and hybrid techniques to provide dynamic decision-making and resilience. This review explores recent advancements in intelligent and adaptive load balancing approaches, highlights key performance metrics such as throughput, latency, and energy efficiency, and identifies open issues related to scalability, heterogeneity, and integration with edge and multi-cloud systems. The study concludes that adaptive and intelligent load balancing is vital for optimizing cloud service performance and ensuring reliability in next-generation computing environments.
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