Experimental assessment of traffic prediction assisted data center network reconfiguration method

Xiaotao Guo; Xuwei Xue; Fulong Yan; Bitao Pan; Georgios Exarchakos; Nicola Calabretta

doi:10.1109/ECOC52684.2021.9606079

Experimental assessment of traffic prediction assisted data center network reconfiguration method

Xiaotao Guo, Xuwei Xue, Fulong Yan, Bitao Pan, Georgios Exarchakos, Nicola Calabretta

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

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We experimentally demonstrate a traffic prediction assisted network reconfiguration method (TPANR) for data center networks based on deep reinforcement learning (DRL). Traffic prediction model performs the lowest MSE of 2.64E-4. Exploiting one-step ahead traffic prediction and DRL-based automatic network reconfiguration, TPANR achieves 17.3% latency improvement.

Originele taal-2	Engels
Titel	2021 European Conference on Optical Communication (ECOC)
Uitgeverij	Institute of Electrical and Electronics Engineers
Aantal pagina's	4
ISBN van elektronische versie	978-1-6654-3868-1
DOI's	https://doi.org/10.1109/ECOC52684.2021.9606079
Status	Gepubliceerd - 22 nov. 2021
Evenement	47th European Conference on Optical Communications, ECOC 2021 - Bordeaux, Frankrijk Duur: 13 sep. 2021 → 16 sep. 2021 Congresnummer: 47

Congres

Congres	47th European Conference on Optical Communications, ECOC 2021
Verkorte titel	ECOC 2021
Land/Regio	Frankrijk
Stad	Bordeaux
Periode	13/09/21 → 16/09/21

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© 2021 IEEE.

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@inproceedings{b2394543757244a38e512f84b42aa64b,

title = "Experimental assessment of traffic prediction assisted data center network reconfiguration method",

abstract = "We experimentally demonstrate a traffic prediction assisted network reconfiguration method (TPANR) for data center networks based on deep reinforcement learning (DRL). Traffic prediction model performs the lowest MSE of 2.64E-4. Exploiting one-step ahead traffic prediction and DRL-based automatic network reconfiguration, TPANR achieves 17.3% latency improvement.",

author = "Xiaotao Guo and Xuwei Xue and Fulong Yan and Bitao Pan and Georgios Exarchakos and Nicola Calabretta",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 47th European Conference on Optical Communications, ECOC 2021, ECOC 2021 ; Conference date: 13-09-2021 Through 16-09-2021",

year = "2021",

month = nov,

day = "22",

doi = "10.1109/ECOC52684.2021.9606079",

language = "English",

booktitle = "2021 European Conference on Optical Communication (ECOC)",

publisher = "Institute of Electrical and Electronics Engineers",

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}

Guo, X, Xue, X , Yan, F, Pan, B, Exarchakos, G & Calabretta, N 2021, Experimental assessment of traffic prediction assisted data center network reconfiguration method. in 2021 European Conference on Optical Communication (ECOC)., 9606079, Institute of Electrical and Electronics Engineers, 47th European Conference on Optical Communications, ECOC 2021, Bordeaux, Frankrijk, 13/09/21. https://doi.org/10.1109/ECOC52684.2021.9606079

Experimental assessment of traffic prediction assisted data center network reconfiguration method. / Guo, Xiaotao; Xue, Xuwei ; Yan, Fulong et al.
2021 European Conference on Optical Communication (ECOC). Institute of Electrical and Electronics Engineers, 2021. 9606079.

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

TY - GEN

T1 - Experimental assessment of traffic prediction assisted data center network reconfiguration method

AU - Guo, Xiaotao

AU - Xue, Xuwei

AU - Yan, Fulong

AU - Pan, Bitao

AU - Exarchakos, Georgios

AU - Calabretta, Nicola

N1 - Conference code: 47

PY - 2021/11/22

Y1 - 2021/11/22

N2 - We experimentally demonstrate a traffic prediction assisted network reconfiguration method (TPANR) for data center networks based on deep reinforcement learning (DRL). Traffic prediction model performs the lowest MSE of 2.64E-4. Exploiting one-step ahead traffic prediction and DRL-based automatic network reconfiguration, TPANR achieves 17.3% latency improvement.

AB - We experimentally demonstrate a traffic prediction assisted network reconfiguration method (TPANR) for data center networks based on deep reinforcement learning (DRL). Traffic prediction model performs the lowest MSE of 2.64E-4. Exploiting one-step ahead traffic prediction and DRL-based automatic network reconfiguration, TPANR achieves 17.3% latency improvement.

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U2 - 10.1109/ECOC52684.2021.9606079

DO - 10.1109/ECOC52684.2021.9606079

M3 - Conference contribution

AN - SCOPUS:85123220218

BT - 2021 European Conference on Optical Communication (ECOC)

PB - Institute of Electrical and Electronics Engineers

T2 - 47th European Conference on Optical Communications, ECOC 2021

Y2 - 13 September 2021 through 16 September 2021

ER -

Experimental assessment of traffic prediction assisted data center network reconfiguration method

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