Network Resource Management Drives Machine Learning: A Survey and Future Research Direction

Wasswa Shafik, Mojtaba Matinkhah, Mamman Nur Sanda


Network resource management is one of the vibrant factors in the current dynamic technological computing paradigms. This reduces poor resource utilization; network resources include network devices, management networks, management systems, and management support organizations carrying out task planning, resource scheduling, and network managing among many more. It's now been observed within different networks that machine learning has been applied to help in carrying some network tasks. This paper surveys current approaches that have been done in managing resources with a deep focus on energy optimization, auto-scaling methods based on current machine learning approaches. We further present the proposed techniques that are identified by evolving this overview by investigating other state-of-the-art recommendations. This study provides a deep insight into proposed methods, loopholes that will aid researchers to design, model, or create novel frameworks that focus on the better options of resource management in contrast to the existing methods.


Resources Management; 5G Networks; SDN; NFV; Auto scaling Method; Machine Learning

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