Big data analytics for the virtual network topology reconfiguration use case
Document typeConference report
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Rights accessRestricted access - publisher's policy
ABNO's OAM Handler is extended with big data analytics capabilities to anticipate traffic changes in volume and direction. Predicted traffic is used to trigger virtual network topology re-optimization. When the virtual topology needs to be reconfigured, predicted and current traffic matrices are used to find the optimal topology. A heuristic algorithm to adapt current virtual topology to meet both actual demands and expected traffic matrix is proposed. Experimental assessment is carried out on UPC's SYNERGY testbed.
CitationGifre, L., Morales, F., Velasco, L., Ruiz, M. Big data analytics for the virtual network topology reconfiguration use case. A: International Conference on Transparent Optical Networks. "2016 18th International Conference on Transparent Optical Networks (ICTON 2016): Trento, Italy: 10-14 July 2016". Trento: Institute of Electrical and Electronics Engineers (IEEE), 2016.