A LOAD BALANCING ALGORITHM FOR THE DATA CENTERS TO OPTIMIZE CLOUD COMPUTING APPLICATION

Abstract

Cloud computing has emerged as a foundational technology for delivering scalable, flexible, and cost-effective computing services. However, with increasing user demands and dynamic workloads, ensuring efficient resource utilization and performance in cloud data centers becomes a critical challenge. One of the major issues in cloud environments is uneven load distribution, which can lead to resource underutilization, increased response time, and degraded quality of service (QoS). This project proposes a novel load balancing algorithm for data centers that intelligently distributes incoming tasks across available virtual machines (VMs) to achieve optimized performance and resource allocation. The algorithm uses real-time monitoring and heuristic or machine learning-based decision-making to balance workloads efficiently. The goal is to improve throughput, reduce latency, and maintain service-level agreements (SLAs) while minimizing energy consumption and operational costs in cloud computing environments