Using deep learning for recommending and completing deployment descriptors in nfv

Wassim Sellil Atoui; Imen Grida Ben Yahia; Walid Gaaloul

doi:10.1109/NETSOFT.2019.8806704

Using deep learning for recommending and completing deployment descriptors in nfv

Wassim Sellil Atoui, Imen Grida Ben Yahia, Walid Gaaloul

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Future software networks promises to fully automate the network management, configuration, deployment and operations of devices. Currently the deployment automation is enabled by orchestrators using descriptor files associated with Virtual Network Functions (VNFs) and Network Services (NSs), called VNF Descriptors (VNFDs) and NS Descriptors (NSDs). We focus our attention in this demo paper on VNFDs and we propose a framework for VNFD-Mining with Word Embeddings and Deep Neural Networks. The aim of the framework is to augment orchestrators with an ability to select, recommend and complete NFV descriptors given an initial description. The framework is trained initially with a catalogue of predefined VNFDs.

Original language	English
Title of host publication	Proceedings of the 2019 IEEE Conference on Network Softwarization
Subtitle of host publication	Unleashing the Power of Network Softwarization, NetSoft 2019
Editors	Christian Jacquenet, Filip De Turck, Prosper Chemouil, Flavio Esposito, Olivier Festor, Walter Cerroni, Stefano Secci
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	233-235
Number of pages	3
ISBN (Electronic)	9781538693766
DOIs	https://doi.org/10.1109/NETSOFT.2019.8806704
Publication status	Published - 1 Jun 2019
Externally published	Yes
Event	5th IEEE Conference on Network Softwarization, NetSoft 2019 - Paris, France Duration: 24 Jun 2019 → 28 Jun 2019

Publication series

Name	Proceedings of the 2019 IEEE Conference on Network Softwarization: Unleashing the Power of Network Softwarization, NetSoft 2019

Conference

Conference	5th IEEE Conference on Network Softwarization, NetSoft 2019
Country/Territory	France
City	Paris
Period	24/06/19 → 28/06/19

Access to Document

10.1109/NETSOFT.2019.8806704

Cite this

Atoui, W. S., Ben Yahia, I. G., & Gaaloul, W. (2019). Using deep learning for recommending and completing deployment descriptors in nfv. In C. Jacquenet, F. De Turck, P. Chemouil, F. Esposito, O. Festor, W. Cerroni, & S. Secci (Eds.), Proceedings of the 2019 IEEE Conference on Network Softwarization: Unleashing the Power of Network Softwarization, NetSoft 2019 (pp. 233-235). Article 8806704 (Proceedings of the 2019 IEEE Conference on Network Softwarization: Unleashing the Power of Network Softwarization, NetSoft 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/NETSOFT.2019.8806704

Atoui, Wassim Sellil ; Ben Yahia, Imen Grida ; Gaaloul, Walid. / Using deep learning for recommending and completing deployment descriptors in nfv. Proceedings of the 2019 IEEE Conference on Network Softwarization: Unleashing the Power of Network Softwarization, NetSoft 2019. editor / Christian Jacquenet ; Filip De Turck ; Prosper Chemouil ; Flavio Esposito ; Olivier Festor ; Walter Cerroni ; Stefano Secci. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 233-235 (Proceedings of the 2019 IEEE Conference on Network Softwarization: Unleashing the Power of Network Softwarization, NetSoft 2019).

@inproceedings{7c373087ee2048998966befdc0aeb13b,

title = "Using deep learning for recommending and completing deployment descriptors in nfv",

abstract = "Future software networks promises to fully automate the network management, configuration, deployment and operations of devices. Currently the deployment automation is enabled by orchestrators using descriptor files associated with Virtual Network Functions (VNFs) and Network Services (NSs), called VNF Descriptors (VNFDs) and NS Descriptors (NSDs). We focus our attention in this demo paper on VNFDs and we propose a framework for VNFD-Mining with Word Embeddings and Deep Neural Networks. The aim of the framework is to augment orchestrators with an ability to select, recommend and complete NFV descriptors given an initial description. The framework is trained initially with a catalogue of predefined VNFDs.",

author = "Atoui, \{Wassim Sellil\} and \{Ben Yahia\}, \{Imen Grida\} and Walid Gaaloul",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 5th IEEE Conference on Network Softwarization, NetSoft 2019 ; Conference date: 24-06-2019 Through 28-06-2019",

year = "2019",

month = jun,

day = "1",

doi = "10.1109/NETSOFT.2019.8806704",

language = "English",

series = "Proceedings of the 2019 IEEE Conference on Network Softwarization: Unleashing the Power of Network Softwarization, NetSoft 2019",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "233--235",

editor = "Christian Jacquenet and \{De Turck\}, Filip and Prosper Chemouil and Flavio Esposito and Olivier Festor and Walter Cerroni and Stefano Secci",

booktitle = "Proceedings of the 2019 IEEE Conference on Network Softwarization",

}

Atoui, WS, Ben Yahia, IG & Gaaloul, W 2019, Using deep learning for recommending and completing deployment descriptors in nfv. in C Jacquenet, F De Turck, P Chemouil, F Esposito, O Festor, W Cerroni & S Secci (eds), Proceedings of the 2019 IEEE Conference on Network Softwarization: Unleashing the Power of Network Softwarization, NetSoft 2019., 8806704, Proceedings of the 2019 IEEE Conference on Network Softwarization: Unleashing the Power of Network Softwarization, NetSoft 2019, Institute of Electrical and Electronics Engineers Inc., pp. 233-235, 5th IEEE Conference on Network Softwarization, NetSoft 2019, Paris, France, 24/06/19. https://doi.org/10.1109/NETSOFT.2019.8806704

Using deep learning for recommending and completing deployment descriptors in nfv. / Atoui, Wassim Sellil; Ben Yahia, Imen Grida; Gaaloul, Walid.
Proceedings of the 2019 IEEE Conference on Network Softwarization: Unleashing the Power of Network Softwarization, NetSoft 2019. ed. / Christian Jacquenet; Filip De Turck; Prosper Chemouil; Flavio Esposito; Olivier Festor; Walter Cerroni; Stefano Secci. Institute of Electrical and Electronics Engineers Inc., 2019. p. 233-235 8806704 (Proceedings of the 2019 IEEE Conference on Network Softwarization: Unleashing the Power of Network Softwarization, NetSoft 2019).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - Future software networks promises to fully automate the network management, configuration, deployment and operations of devices. Currently the deployment automation is enabled by orchestrators using descriptor files associated with Virtual Network Functions (VNFs) and Network Services (NSs), called VNF Descriptors (VNFDs) and NS Descriptors (NSDs). We focus our attention in this demo paper on VNFDs and we propose a framework for VNFD-Mining with Word Embeddings and Deep Neural Networks. The aim of the framework is to augment orchestrators with an ability to select, recommend and complete NFV descriptors given an initial description. The framework is trained initially with a catalogue of predefined VNFDs.

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BT - Proceedings of the 2019 IEEE Conference on Network Softwarization

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Atoui WS, Ben Yahia IG, Gaaloul W. Using deep learning for recommending and completing deployment descriptors in nfv. In Jacquenet C, De Turck F, Chemouil P, Esposito F, Festor O, Cerroni W, Secci S, editors, Proceedings of the 2019 IEEE Conference on Network Softwarization: Unleashing the Power of Network Softwarization, NetSoft 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 233-235. 8806704. (Proceedings of the 2019 IEEE Conference on Network Softwarization: Unleashing the Power of Network Softwarization, NetSoft 2019). doi: 10.1109/NETSOFT.2019.8806704

Using deep learning for recommending and completing deployment descriptors in nfv

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