"An approach to network slice selection function for multi-domain environments on 5G mobile networks and future communication systems.
The Network Slice Selection Function (NSSF) in heterogeneous technology environments is a complex problem, which still does not have a fully acceptable solution. Thus, the implementation of new network selection strategies represents an important issue in development, mainly due to the growing demand for applications and scenarios involving 5G and future networks. This work then presents an integrated solution for the NSSF problem, called Network Slice Selection Function Decision-Aid Framework (NSSF DAF), which consists of a distributed solution in which a part is executed on the users equipment (e.g. smartphones, Unmanned Aerial Vehicles, IoT brokers), functioning as a transparent service, and another at the Edge of the operator or service provider. It requires low consumption of computing resources from mobile devices and offers complete independence from the network operator. For this purpose, protocols and software tools are used to classify slices. This work employs fourteen multicriteria methods to aid decision-making: ARAS, COCOSO, CODAS, COPRAS, EDAS, MABAC, MAIRCA, MARCOS, MOORA, OCRA, PROMETHEE II, SPOTIS, TOPSIS and VIKOR. The general objective is to verify the similarity among these methods and applications in the slice classification and selection process, considering a specific scenario, towards the framework. It also uses machine learning through the K-means clustering algorithm, adopting a hybrid solution to implement and operate the NSSF service in multi-domain slicing environments of heterogeneous mobile networks. Testbeds were conducted to validate the proposed framework, mapping the adequate quality of service requirements. The results indicate a real possibility of offering a complete solution to the NSSF problem that can be implemented in Edge, in Core, or even in 5G Radio Base Station itself, without the incremental computational cost of the end users equipment, allowing the adequate quality of experience."
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