Field trial of Machine-Learning-assisted and SDN-based Optical Network Planning with Network-Scale Monitoring Database

Shuangyi Yan; N. Khan Khan; Alex Mavromatis; Dimitrios Gkounis; Qirui Fan; Foteini Ntavou; Konstantinos Nikolovgenis; Fanchao Meng; Emilio Hugues Salas; Changjian Guo; Chao Lu; Alan Pak Tau Lau; Reza Nejabati; Dimitra Simeonidou

doi:10.1109/ECOC.2017.8346091

Field trial of Machine-Learning-assisted and SDN-based Optical Network Planning with Network-Scale Monitoring Database

Shuangyi Yan, N. Khan Khan, Alex Mavromatis, Dimitrios Gkounis, Qirui Fan, Foteini Ntavou, Konstantinos Nikolovgenis, Fanchao Meng, Emilio Hugues Salas, Changjian Guo, Chao Lu, Alan Pak Tau Lau, Reza Nejabati, Dimitra Simeonidou

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

71 Citations (Scopus)

594 Downloads (Pure)

Abstract

An SDN based network planning framework utilizing machine-learning techniques, network configuration and monitoring database is implemented over an optical field-trial testbed comprised of 436.4-km fibre. Adaption of the spectral efficiency utilising probabilistic-shaping BVT based on link performance prediction is demonstrated.

Original language	English
Title of host publication	2017 43rd European Conference and Exhibition on Optical Communication (ECOC 2017)
Subtitle of host publication	Proceedings of a meeting held 17-21 September 2017, Gothenburg, Sweden
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	793-795
Number of pages	3
ISBN (Electronic)	9781538656242
ISBN (Print)	9781538649930
DOIs	https://doi.org/10.1109/ECOC.2017.8346091
Publication status	Published - Jun 2018

Access to Document

10.1109/ECOC.2017.8346091

Full-text PDF (accepted author manuscript)
This is the author accepted manuscript (AAM). The final published version (version of record) is available online via IEEE at https://ieeexplore.ieee.org/document/8346091 . Please refer to any applicable terms of use of the publisher.
Accepted author manuscript, 1.34 MB

Handle.net

Persistent link

Optical layer abstraction
Simeonidou, D.
31/12/14 → 31/12/18
Project: Research
EPSRC National Dark Fibre Infrastructure Service
Simeonidou, D.
1/11/13 → 30/04/19
Project: Research

Cite this

Yan, S., Khan, N. K., Mavromatis, A., Gkounis, D., Fan, Q., Ntavou, F., Nikolovgenis, K., Meng, F., Salas, E. H., Guo, C., Lu, C., Lau, A. P. T., Nejabati, R., & Simeonidou, D. (2018). Field trial of Machine-Learning-assisted and SDN-based Optical Network Planning with Network-Scale Monitoring Database. In 2017 43rd European Conference and Exhibition on Optical Communication (ECOC 2017): Proceedings of a meeting held 17-21 September 2017, Gothenburg, Sweden (pp. 793-795). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ECOC.2017.8346091

Yan, Shuangyi ; Khan, N. Khan ; Mavromatis, Alex et al. / Field trial of Machine-Learning-assisted and SDN-based Optical Network Planning with Network-Scale Monitoring Database. 2017 43rd European Conference and Exhibition on Optical Communication (ECOC 2017): Proceedings of a meeting held 17-21 September 2017, Gothenburg, Sweden. Institute of Electrical and Electronics Engineers (IEEE), 2018. pp. 793-795

@inproceedings{d6703d8ea0114234877b8e674424db1c,

title = "Field trial of Machine-Learning-assisted and SDN-based Optical Network Planning with Network-Scale Monitoring Database",

abstract = "An SDN based network planning framework utilizing machine-learning techniques, network configuration and monitoring database is implemented over an optical field-trial testbed comprised of 436.4-km fibre. Adaption of the spectral efficiency utilising probabilistic-shaping BVT based on link performance prediction is demonstrated.",

author = "Shuangyi Yan and Khan, {N. Khan} and Alex Mavromatis and Dimitrios Gkounis and Qirui Fan and Foteini Ntavou and Konstantinos Nikolovgenis and Fanchao Meng and Salas, {Emilio Hugues} and Changjian Guo and Chao Lu and Lau, {Alan Pak Tau} and Reza Nejabati and Dimitra Simeonidou",

year = "2018",

month = jun,

doi = "10.1109/ECOC.2017.8346091",

language = "English",

isbn = "9781538649930",

pages = "793--795",

booktitle = "2017 43rd European Conference and Exhibition on Optical Communication (ECOC 2017)",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

address = "United States",

}

Yan, S, Khan, NK, Mavromatis, A, Gkounis, D, Fan, Q, Ntavou, F, Nikolovgenis, K, Meng, F, Salas, EH, Guo, C, Lu, C, Lau, APT, Nejabati, R & Simeonidou, D 2018, Field trial of Machine-Learning-assisted and SDN-based Optical Network Planning with Network-Scale Monitoring Database. in 2017 43rd European Conference and Exhibition on Optical Communication (ECOC 2017): Proceedings of a meeting held 17-21 September 2017, Gothenburg, Sweden. Institute of Electrical and Electronics Engineers (IEEE), pp. 793-795. https://doi.org/10.1109/ECOC.2017.8346091

Field trial of Machine-Learning-assisted and SDN-based Optical Network Planning with Network-Scale Monitoring Database. / Yan, Shuangyi; Khan, N. Khan; Mavromatis, Alex et al.
2017 43rd European Conference and Exhibition on Optical Communication (ECOC 2017): Proceedings of a meeting held 17-21 September 2017, Gothenburg, Sweden. Institute of Electrical and Electronics Engineers (IEEE), 2018. p. 793-795.

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

TY - GEN

T1 - Field trial of Machine-Learning-assisted and SDN-based Optical Network Planning with Network-Scale Monitoring Database

AU - Yan, Shuangyi

AU - Khan, N. Khan

AU - Mavromatis, Alex

AU - Gkounis, Dimitrios

AU - Fan, Qirui

AU - Ntavou, Foteini

AU - Nikolovgenis, Konstantinos

AU - Meng, Fanchao

AU - Salas, Emilio Hugues

AU - Guo, Changjian

AU - Lu, Chao

AU - Lau, Alan Pak Tau

AU - Nejabati, Reza

AU - Simeonidou, Dimitra

PY - 2018/6

Y1 - 2018/6

N2 - An SDN based network planning framework utilizing machine-learning techniques, network configuration and monitoring database is implemented over an optical field-trial testbed comprised of 436.4-km fibre. Adaption of the spectral efficiency utilising probabilistic-shaping BVT based on link performance prediction is demonstrated.

AB - An SDN based network planning framework utilizing machine-learning techniques, network configuration and monitoring database is implemented over an optical field-trial testbed comprised of 436.4-km fibre. Adaption of the spectral efficiency utilising probabilistic-shaping BVT based on link performance prediction is demonstrated.

U2 - 10.1109/ECOC.2017.8346091

DO - 10.1109/ECOC.2017.8346091

M3 - Conference Contribution (Conference Proceeding)

SN - 9781538649930

SP - 793

EP - 795

BT - 2017 43rd European Conference and Exhibition on Optical Communication (ECOC 2017)

PB - Institute of Electrical and Electronics Engineers (IEEE)

ER -

Yan S, Khan NK, Mavromatis A, Gkounis D, Fan Q, Ntavou F et al. Field trial of Machine-Learning-assisted and SDN-based Optical Network Planning with Network-Scale Monitoring Database. In 2017 43rd European Conference and Exhibition on Optical Communication (ECOC 2017): Proceedings of a meeting held 17-21 September 2017, Gothenburg, Sweden. Institute of Electrical and Electronics Engineers (IEEE). 2018. p. 793-795 Epub 2018 Apr 26. doi: 10.1109/ECOC.2017.8346091

Field trial of Machine-Learning-assisted and SDN-based Optical Network Planning with Network-Scale Monitoring Database

Abstract

Access to Document

Handle.net

Fingerprint

Projects

Optical layer abstraction

EPSRC National Dark Fibre Infrastructure Service

Cite this