The Architecture for End-to-End 5G Network Slice Resource Management and Orchestration

A new paradigm is developing in 5G networks in which cloud environments are used to do calculations for different mobile apps. A general computing platform may be realized with the help of compute, storage, as well as networking resources made available by both edge and core clouds. Many services, especially those that are latencysensitive or computationally intensive, might benefit from network slicing techniques in a shared-resource setting. This study recommends a method of resource management for providing the highest possible Quality of Experience (QoE) to users in terms of delayed gap tolerance. The Min-Fit approach is an example of an answer based on heuristics; it finds a server having the most CPU power and places it in charge of meeting customers' demands. A mathematical model for 5G slicing capability is created to optimize the delay gap through resource management and enhance user experience. Several computational experiments serving as performance evaluations demonstrate the efficacy of our proposed strategy for slicing. The results show that our approach is more effective than other algorithms that take more time to complete their tasks.