… Beyond the successes that have already been made, there are still many open issues and
potentials for further successes of machine learning in the field of network slicing resource …

… the network slicing performance. This work aims to design an efficient network slicing using
a hybrid learning … extraction (OWFE), and (c) Slicing classification. First, we collected the 5G …

… (AI) and machine learning based network control and management technologies [4]. …
5G network slicing and elaborate the necessity of automation of network functions for the …

… variety of business situations and network traffic groups that are operating on the same
networks using a network slicing architecture [4]. Because of network slicing, it is possible to build …

… With this information, added to the deterministic allocation function, we can aid the
network slice provider to determine if a new slice will fulfill with the SLA requirements. …

… That being said, before delving deeper in the machine learning techniques applied to network
slicing resource control and management problems, we briefly summarise them in Table 2…

… intelligent network slice LCM, from the slice preparation to their decommissioning, after the
3rd Generation Partnership Project (3GPP) life cycle [29] and covering all network domains (…

… 5G, especially, for network slicing. This study aims to integrate various machine learning (ML) …
an experimental framework for the future SONs and network slicing. Finally, based on this …

… use machine learning to predict the services traffic of each slice, so as to allocate radio
resources to each slice to … allocation with machine learning methods in vehicular network slicing. …

… network capabilities more efficiently and effectively, this paper provides a comprehensive
study on edge-enabled network slicing … on the application of machine learning in edge-sliced …