DocumentCode :
1788124
Title :
Neural network-based autonomous allocation of resources in virtual networks
Author :
Mijumbi, Rashid ; Gorricho, Juan-Luis ; Serrat, Joan ; Claeys, Maxim ; Famaey, Jeroen ; De Turck, Filip
Author_Institution :
Univ. Politec. de Catalunya, Barcelona, Spain
fYear :
2014
fDate :
23-26 June 2014
Firstpage :
1
Lastpage :
6
Abstract :
Network virtualisation has received attention as a way to allow for sharing of physical network resources. Sharing resources involves mapping of virtual nodes and links onto physical nodes and links respectively, and thereafter managing the allocated resources to ensure efficient resource utilisation. In this paper, we apply artificial neural networks for a dynamic, decentralised and autonomous allocation of physical network resources to the virtual networks. 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 approach is evaluated by comparison with two static resource allocation schemes and a reinforcement learning-based approach.
Keywords :
computer networks; neural nets; quality of service; resource allocation; virtualisation; artificial neural networks; decentralised physical network resource allocation; dynamic physical network resource allocation; neural network-based autonomous resource allocation; physical links; physical nodes; quality of service; reinforcement learning-based approach; static resource allocation schemes; substrate network resource utilisation; virtual networks; Artificial neural networks; Delays; Dynamic scheduling; Neurons; Resource management; Substrates; Tin; Artificial neural networks; autonomous systems; network virtualisation; reinforcement learning; resource allocation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Networks and Communications (EuCNC), 2014 European Conference on
Conference_Location :
Bologna
Type :
conf
DOI :
10.1109/EuCNC.2014.6882668
Filename :
6882668
Link To Document :
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