CROSS-SYSTEM ANALYSIS OF QUEUEING SYSTEMS INTERACTIONS IN DISTRIBUTED NETWORKS, SUCH AS CLOUD COMPUTING

Abstract

The increasing reliance on cloud computing has brought both remarkable opportunities and complex challenges. Distributed networks, such as cloud computing environments, are inherently dynamic and require robust systems to handle varying workloads efficiently. This study explores the intricate interactions between multiple queueing models within these systems, providing a fresh perspective on their impact on performance. By using queueing theory, we delve into key metrics like response time and resource allocation strategies. Our analysis highlights the advantages of horizontal scaling, vertical scaling, and the critical role of network bandwidth in optimizing cloud infrastructure performance. The findings not only demonstrate the practical applications of queueing theory but also emphasize its value in addressing real-world challenges in distributed networks. This research lays the groundwork for future explorations into predictive models and hybrid approaches, paving the way for smarter, more scalable cloud solutions