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Neural network-based autonomous allocation of resources in virtual networks

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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
Artificial neural networks, IBCN, network virtualisation, resource allocation, reinforcement learning, autonomous systems

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Citation

Please use this url to cite or link to this publication:

MLA
Mijumbi, R et al. “Neural Network-based Autonomous Allocation of Resources in Virtual Networks.” 2014 EUROPEAN CONFERENCE ON NETWORKS AND COMMUNICATIONS (EUCNC). 2014. 1–6. Print.
APA
Mijumbi, R, Gorricho, J.-L., Serrat, J., Claeys, M., Famaey, J., & De Turck, F. (2014). Neural network-based autonomous allocation of resources in virtual networks. 2014 EUROPEAN CONFERENCE ON NETWORKS AND COMMUNICATIONS (EUCNC) (pp. 1–6). Presented at the European Conference on Networks and Communications (EuCNC).
Chicago author-date
Mijumbi, R, J-L Gorricho, J Serrat, Maxim Claeys, Jeroen Famaey, and Filip De Turck. 2014. “Neural Network-based Autonomous Allocation of Resources in Virtual Networks.” In 2014 EUROPEAN CONFERENCE ON NETWORKS AND COMMUNICATIONS (EUCNC), 1–6.
Chicago author-date (all authors)
Mijumbi, R, J-L Gorricho, J Serrat, Maxim Claeys, Jeroen Famaey, and Filip De Turck. 2014. “Neural Network-based Autonomous Allocation of Resources in Virtual Networks.” In 2014 EUROPEAN CONFERENCE ON NETWORKS AND COMMUNICATIONS (EUCNC), 1–6.
Vancouver
1.
Mijumbi R, Gorricho J-L, Serrat J, Claeys M, Famaey J, De Turck F. Neural network-based autonomous allocation of resources in virtual networks. 2014 EUROPEAN CONFERENCE ON NETWORKS AND COMMUNICATIONS (EUCNC). 2014. p. 1–6.
IEEE
[1]
R. Mijumbi, J.-L. Gorricho, J. Serrat, M. Claeys, J. Famaey, and F. De Turck, “Neural network-based autonomous allocation of resources in virtual networks,” in 2014 EUROPEAN CONFERENCE ON NETWORKS AND COMMUNICATIONS (EUCNC), Bologna, Italy, 2014, pp. 1–6.
@inproceedings{5733104,
  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.},
  author       = {Mijumbi, R and Gorricho, J-L and Serrat, J and Claeys, Maxim and Famaey, Jeroen and De Turck, Filip},
  booktitle    = {2014 EUROPEAN CONFERENCE ON NETWORKS AND COMMUNICATIONS (EUCNC)},
  isbn         = {9781479952809},
  keywords     = {Artificial neural networks,IBCN,network virtualisation,resource allocation,reinforcement learning,autonomous systems},
  language     = {eng},
  location     = {Bologna, Italy},
  pages        = {1--6},
  title        = {Neural network-based autonomous allocation of resources in virtual networks},
  year         = {2014},
}

Web of Science
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