Controle de admissão para network slicing considerando recursos de comunicação e computação

• Autor(a) principal: Lima, Henrique Valle de
• Data de Publicação: 2023
• Tipo de documento: Tese
• Idioma: por
• Título da fonte: Repositório Institucional da UFG
• Texto Completo: http://repositorio.bc.ufg.br/tede/handle/tede/12872
• topic: Network slicing; Multi-access edge computing; Multi- armed bandits; 5G; Controle de admissão; CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO

The 5G networks have enabled the application of various innovative and disruptive technologies such as Network Function Virtualization (NFV) and Software-Defined Networking (SDN). Together, these technologies act as enablers of Network Slicing (NS), transforming the way networks are operated, managed, and monetized. Through the concept of Slice-as-a-Service (SlaaS), telecommunications operators can monetize the physical and logical infrastructure by offering network slices to new customers, such as vertical industries. This thesis addresses the problem of tenant admission control using NS. We propose three admission control models for NS (MONETS-OBD, MONETS-OBS, and CAONS) that consider both communication and computation resources. To evaluate the proposed models, we compare the results with different classical algorithms from the literature, such as eUCB, e-greedy, and ONETS. We use data from different applications to enrich the analysis. The results indicate that the MONETS-OBD, MONETS-OBS, and CAONS heuristics perform admission control that approaches the set of ideal solutions. We achieve high efficiency with the MONETS-OBD and MONETS-OBS heuristics in controlling tenant admission, reaching acceptance rates of up to 99% in some cases. Furthermore, the CAONS heuristic, which employs penalties, not only achieves acceptance and reward rates close to the optimal solution but also significantly reduces the number of capacity violations. Lastly, the results highlight that the process of slice admission control should consider both communication and computation resources, which are scarce at the network edge. A solution that considers only communication resources can lead to incorrect and unfeasible interpretations, overestimating the capacity of computation resources.