Banca de QUALIFICAÇÃO: FELIPE SAMPAIO DANTAS DA SILVA

Uma banca de QUALIFICAÇÃO de DOUTORADO foi cadastrada pelo programa.
STUDENT : FELIPE SAMPAIO DANTAS DA SILVA
DATE: 29/07/2021
TIME: 10:00
LOCAL: https://meet.google.com/znv-eksf-wsv
TITLE:

Cloud-Network Slicing-driven Intelligent Mobility Control in Federated 5G Infrastructures


KEY WORDS:

5G, Cloud-Network Slicing, Mobility Control, Machine Learning, Handover


PAGES: 80
BIG AREA: Ciências Exatas e da Terra
AREA: Ciência da Computação
SUBÁREA: Sistemas de Computação
SPECIALTY: Teleinformática
SUMMARY:

The 5th generation of mobile networks (5G) is designed to provide high connectivity capacity in terms of coverage and support for a larger diversity of service types, traffic, and users (User Equipment - UE) with diverse mobility patterns and critical Quality of Service (QoS) requirements. By incorporating new technologies such as Cloud Computing and Mobile Edge Computing (MEC), 5G infrastructures will increase network and cloud capabilities within the Radio Access Networks (RAN) closer to end-users, allowing high content and service delivery flexibility. In this context, new paradigms such as Network Slicing (NS) have been widely adopted for the ability to enable the infrastructure to deploy services in a personalized and elastic way, promoted through a set of network resource components that can be extended through physical resource virtualization strategies and softwarization. Recently, the Cloud-Network Slicing (CNS) approach was introduced as an alternative to meet the demands of industry verticals, which offer their services across multiple administrative and technological domains distributed across the federated cloud and network infrastructures. In this scenario, characterized by the inevitability of handover between the various cells existing in the RAN, the infrastructure management system must be extended with improved capabilities to maintain the UE experience during mobility events, benefiting from the ability of slicing to orchestrate resources available in a cloud ecosystem to deliver a service with seamless connectivity in a transparent and agile manner. Therefore, it is necessary to rethink traditional mobility management approaches to direct their operating model in infrastructures defined by CNS to advance mobile services on 5G networks. A recent survey of the literature revealed works that promote mobility management in systems defined by NSs and the inexistence of mechanisms driven by CNS. Furthermore, existing mechanisms manage the mobility of entities associated with NSs considering classical models based on signal strength. However, in systems defined by CNS, decision mechanisms require complete knowledge of active CNS instances, their computational and network requirements, operational services, service-consuming nodes, among other aspects. The research developed in this Ph.D. thesis intends to fill this gap and pave 5G systems defined by CNS from an approach with automated and proactive mobility control and management capabilities in 5G systems. The main contributions of this research include: (i) broad review and discussion on quality-oriented handover decision mechanisms in compliance with the critical requirements imposed by 5G verticals in CNS defined systems; (ii) an automated and proactive approach to mobility management guided by CNS, capable of maintaining mobile users of CNS instances always best connected and served, respecting the end-to-end definitions and the high level of isolation; (iii) provide compliance-driven mobility control of CNS resources and UEs QoS requirements to act as a trigger for network re-orchestration events (e.g., mobility load balancing); (iv) intelligent mobility prediction and decision to enable UEs (not necessarily in transit) with seamless and transparent connectivity while selecting the best access point for CNS services.


BANKING MEMBERS:
Presidente - 1699087 - AUGUSTO JOSE VENANCIO NETO
Externo ao Programa - 3139050 - ROGER KREUTZ IMMICH
Externo à Instituição - EDMUNDO HEITOR DA SILVA MONTEIRO - UC
Notícia cadastrada em: 14/07/2021 16:45
SIGAA | Superintendência de Tecnologia da Informação - | | Copyright © 2006-2022 - UFRN - sigaa25-producao.info.ufrn.br.sigaa25-producao