Optimizing Performance of Cloud Computing Management Algorithm for High-Traffic Networks

Cloud computing has revolutionized the way people use technology, enabling a variety of virtual services and applications in the corporate world. The improved cost-efficiency and flexibility of cloud computing have made it an attractive option for companies that require high-traffic networks. However, this has also increased the need for optimizing network performance in order to ensure reliable service and a pleasing experience for users. To this end, various algorithms have been proposed for cloud computing management. However, these algorithms often conflict with each other, leading to a decrease in performance. Thus, there is a need for a unified approach that can take into account different methods in a holistic manner. The optimization algorithms developed for cloud computing management are targeted towards improving resource utilization, failure handling, and load balancing. By properly allocating and balancing resources, the overhead associated with these tasks is greatly reduced. Furthermore, the intelligent use of techniques such as fault tolerance, capacity planning, and quality of service guarantees ensures that the users' experience within the cloud is of optimal quality. Parametric results from research on Cloud Computing management algorithm performance showed that, when correctly implemented, the algorithms can provide significant improvements to the management and performance of high-traffic networks. Specifically, performance improvements up to 40% were observed in resource allocation speed and energy consumption.