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Título:
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A neuro-fuzzy approach to self-management of virtual network resources
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Autor/a:
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Mijumbi, Rashid; Gorricho Moreno, Juan Luis; Serrat Fernández, Juan; Shen, Meng; Xu, Ke; Yang, Kun
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Otros autores:
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Universitat Politècnica de Catalunya. Departament d'Enginyeria Telemàtica; Universitat Politècnica de Catalunya. MAPS - Gestió, Polítiques de Preus i Serveis en Xarxes de Nova Generació |
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Abstract:
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Network virtualisation promises to lead to better manageability of the future Internet by allowing for adaptable sharing of physical network resources among different virtual networks. However, the sharing
of resources is not trivial as virtual nodes and links should first be mapped onto substrate nodes and links, and thereafter the allocated resources managed throughout the lifetime of the virtual network. In this
paper, we design and evaluate reinforcement learning-based neuro-fuzzy algorithms that perform dynamic, decentralised and coordinated self-management of substrate network resources. The objective is to achieve better efficiency in the utilisation of substrate network resources while ensuring that the quality of service requirements of the virtual networks are not violated. The proposed algorithms are evaluated through comparisons with a Q-learning-based approach as well as two static resource allocation schemes. |
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Abstract:
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Peer Reviewed |
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Materia(s):
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-Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Telemàtica i xarxes d'ordinadors
-Neural networks (Computer science)
-Fuzzy systems
-Neural networks
-Fuzzy systems
-Neuro-fuzzy systems
-Reinforcement learning
-Network virtualisation
-Dynamic resource allocation
-Multi-agent systems
-Autonomous systems
-Future Internet
-Xarxes neuronals (Informàtica)
-Sistemes borrosos |
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Derechos:
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Tipo de documento:
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Artículo - Versión publicada
Artículo |
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