Optimizing Cloud Computing Resources through AI-driven Load Balancing

Abstract

This study presents an artificial intelligence-based approach to optimize the allocation of resources in cloud computing environments. By employing advanced load balancing algorithms, the research aims to minimize latency and maximize the efficiency of resource utilization. The proposed system dynamically adjusts resource distribution based on real-time data analytics, leading to enhanced performance of cloud-hosted applications. Our results demonstrate significant improvements in computational efficiency and service delivery, suggesting a versatile model applicable to various cloud service architectures.