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Título
A Framework for Next Generation Cloud-Native SDN Cognitive Resource Orchestrator for IoTs (NG2CRO)
Autor
Año del Documento
2023
Editorial
Springer
Descripción
Producción Científica
Documento Fuente
In: Mehmood, R., et al. Distributed Computing and Artificial Intelligence, Special Sessions I, 20th International Conference. DCAI 2023. Lecture Notes in Networks and Systems vol. 741, pp. 399-407, Springer, Cham
Abstract
SDN (Software Define Networking) and NFV (Network Function Virtualization) are the key enablers for 5G systems and also open many doors in the cloud-native application. Besides, it invites new challenges to the efficiency and scalability of resource management. This work aims to provide a cognitive framework for 5G resource and service orchestration in a cloud-native SDN environment. The proposed NG2CRO framework resource orchestrator is designed to adapt the network’s self-learning capabilities and dynamicity while taken on to account the network’s Markovian properties and diverse service requirements. We consider incorporating AI (Artificial Intelligence) techniques specifically RL (Reinforcement Learning) methodologies because literature has shown that these techniques can efficiently address and comply with the current dynamic behaviors and heterogeneity of 5G services and applications. In conclusion, both benefits and liabilities are discussed of incorporating AI specifically RL into resource orchestration practices that provide us with future research challenges.
Palabras Clave
Next Generation 5G Network
Artificial Intelligence
Network Automation
Software-Define Networking
Cloud-Native SDN
Resource Orchestration
Patrocinador
EU H2020 MSCA ITN-ETN IoTalentum (grant no. 953442)
Consejería de Educación de la Junta de Castilla y León y FEDER (VA231P20)
Ministerio de Ciencia e Innovación y Agencia Estatal de Investigación (Proyecto PID2020-112675RB-C42 financiado por MCIN/AEI/10.13039/501100011033)
Consejería de Educación de la Junta de Castilla y León y FEDER (VA231P20)
Ministerio de Ciencia e Innovación y Agencia Estatal de Investigación (Proyecto PID2020-112675RB-C42 financiado por MCIN/AEI/10.13039/501100011033)
Version del Editor
Idioma
eng
Tipo de versión
info:eu-repo/semantics/acceptedVersion
Derechos
openAccess
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