Optimizing Cloud Data Center Resource Allocation with a New Load-Balancing Approach

Abstract

The internet's scalable access to storage, apps, and processing power through cloud computing has completely changed the way IT is managed. With a focus on sophisticated load-balancing strategies, this article investigates the optimization of resource allocation in cloud data centers. Innovation is required since traditional approaches frequently fail in dynamic cloud environments. Utilizing edge computing, AI, and machine learning, we suggest a unique load- balancing strategy that improves scalability, efficiency, and performance. In order to fill in the gaps and maximize resource usage and enhance system responsiveness, this research proposes methods for intelligently distributing workloads between data centers and virtual machines