Collaborative Cross System AI: Toward 5G System and beyond

Miloud Bagaa; Tarik Taleb; Jukka Riekki; Jae Seung Song

doi:10.1109/MNET.011.2000607

Collaborative Cross System AI: Toward 5G System and beyond

Miloud Bagaa, Tarik Taleb, Jukka Riekki, Jae Seung Song^*

^*Tämän työn vastaava kirjoittaja

Tutkimustuotos: Lehtiartikkeli › Article › Scientific › vertaisarvioitu

8 Sitaatiot (Scopus)

128 Lataukset (Pure)

Abstrakti

The emerging industrial verticals set new challenges for 5G and beyond systems. Indeed, the heterogeneity of the underlying technologies and the challenging and conflicting requirements of the verticals make the orchestration and management of networks complicated and challenging. Recent advances in network automation and artificial intelligence (AI) create enthusiasm from industries and academia toward applying these concepts and techniques to tackle these challenges. With these techniques, the network can be autonomously optimized and configured. This article suggests a collaborative cross-system AI that leverages diverse data from different segments involved in the end-to-end communication of a service, diverse AI techniques, and diverse network automation tools to create a self-optimized and self-orchestrated network that can adapt according to the network state. We align the proposed framework with the ongoing network standardization.

Alkuperäiskieli	Englanti
Artikkeli	9409842
Sivut	286-294
Sivumäärä	9
Julkaisu	IEEE Network
Vuosikerta	35
Numero	4
Varhainen verkossa julkaisun päivämäärä	20 huhtik. 2021
DOI - pysyväislinkit	https://doi.org/10.1109/MNET.011.2000607
Tila	Julkaistu - 1 heinäk. 2021
OKM-julkaisutyyppi	A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

Pääsy asiakirjaan

10.1109/MNET.011.2000607

ELEC_Bagaa_etal_Collaborative_Cross_System_AI_IEEE_Network_2021_acceptedauthormanuscriptAccepted author manuscript, 583 KB

Muut tiedostot ja linkit

Linkki julkaisuun Scopuksessa

CSN: Customized Software Networking across Multiple Administrative Domains
Taleb, T. (Vastuullinen tutkija), Addad, R. (Projektin jäsen), Afolabi, I. (Projektin jäsen), Amor, A. (Projektin jäsen), Yu, H. (Projektin jäsen), Kianpisheh, S. (Projektin jäsen), Mariouak, M. (Projektin jäsen), Hellaoui, H. (Projektin jäsen), Sehad, N. (Projektin jäsen), Boudi, A. (Projektin jäsen), El Marai, O. (Projektin jäsen), Shokrnezhad, M. (Projektin jäsen), Bagaa, M. (Projektin jäsen), Maity, I. (Projektin jäsen), Naas, S.-A. (Projektin jäsen), Bekkouche, O. (Projektin jäsen), Benzaid, C. (Projektin jäsen), Kerfah, I. (Projektin jäsen), Mada, B. (Projektin jäsen) & Yang, B. (Projektin jäsen)
01/09/2017 → 31/08/2021
Projekti: Academy of Finland: Other research funding

Siteeraa tätä

@article{5f15bb2ed8a64f4d81354cbbbaa016f6,

title = "Collaborative Cross System AI: Toward 5G System and beyond",

abstract = "The emerging industrial verticals set new challenges for 5G and beyond systems. Indeed, the heterogeneity of the underlying technologies and the challenging and conflicting requirements of the verticals make the orchestration and management of networks complicated and challenging. Recent advances in network automation and artificial intelligence (AI) create enthusiasm from industries and academia toward applying these concepts and techniques to tackle these challenges. With these techniques, the network can be autonomously optimized and configured. This article suggests a collaborative cross-system AI that leverages diverse data from different segments involved in the end-to-end communication of a service, diverse AI techniques, and diverse network automation tools to create a self-optimized and self-orchestrated network that can adapt according to the network state. We align the proposed framework with the ongoing network standardization. ",

author = "Miloud Bagaa and Tarik Taleb and Jukka Riekki and Song, {Jae Seung}",

note = "Funding Information: AcknoWledgment The research leading to these results received funding from the European Union{\textquoteright}s Horizon 2020 research and innovation program under grant agreement no. 101016509 (project CHARITY). The article reflects only the authors{\textquoteright} views. The Commission is not responsible for any use that may be made of the information it contains. The research work is also partially funded by the Academy of Finland 6Genesis project under Grant No. 318927, and by the Academy of Finland CSN project under Grant No. 311654. Prof. Song was supported by the Institute of Information & Communications Technology Planning & Evaluation (IITP) (No. 2020-0-00959). Dr. Miloud Bagaa work was supported by the CSN project. Publisher Copyright: {\textcopyright} 1986-2012 IEEE.",

year = "2021",

month = jul,

day = "1",

doi = "10.1109/MNET.011.2000607",

language = "English",

volume = "35",

pages = "286--294",

journal = "IEEE Network",

issn = "0890-8044",

publisher = "IEEE",

number = "4",

}

TY - JOUR

T1 - Collaborative Cross System AI

T2 - Toward 5G System and beyond

AU - Bagaa, Miloud

AU - Taleb, Tarik

AU - Riekki, Jukka

AU - Song, Jae Seung

N1 - Funding Information: AcknoWledgment The research leading to these results received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement no. 101016509 (project CHARITY). The article reflects only the authors’ views. The Commission is not responsible for any use that may be made of the information it contains. The research work is also partially funded by the Academy of Finland 6Genesis project under Grant No. 318927, and by the Academy of Finland CSN project under Grant No. 311654. Prof. Song was supported by the Institute of Information & Communications Technology Planning & Evaluation (IITP) (No. 2020-0-00959). Dr. Miloud Bagaa work was supported by the CSN project. Publisher Copyright: © 1986-2012 IEEE.

PY - 2021/7/1

Y1 - 2021/7/1

N2 - The emerging industrial verticals set new challenges for 5G and beyond systems. Indeed, the heterogeneity of the underlying technologies and the challenging and conflicting requirements of the verticals make the orchestration and management of networks complicated and challenging. Recent advances in network automation and artificial intelligence (AI) create enthusiasm from industries and academia toward applying these concepts and techniques to tackle these challenges. With these techniques, the network can be autonomously optimized and configured. This article suggests a collaborative cross-system AI that leverages diverse data from different segments involved in the end-to-end communication of a service, diverse AI techniques, and diverse network automation tools to create a self-optimized and self-orchestrated network that can adapt according to the network state. We align the proposed framework with the ongoing network standardization.

AB - The emerging industrial verticals set new challenges for 5G and beyond systems. Indeed, the heterogeneity of the underlying technologies and the challenging and conflicting requirements of the verticals make the orchestration and management of networks complicated and challenging. Recent advances in network automation and artificial intelligence (AI) create enthusiasm from industries and academia toward applying these concepts and techniques to tackle these challenges. With these techniques, the network can be autonomously optimized and configured. This article suggests a collaborative cross-system AI that leverages diverse data from different segments involved in the end-to-end communication of a service, diverse AI techniques, and diverse network automation tools to create a self-optimized and self-orchestrated network that can adapt according to the network state. We align the proposed framework with the ongoing network standardization.

UR - http://www.scopus.com/inward/record.url?scp=85104659552&partnerID=8YFLogxK

U2 - 10.1109/MNET.011.2000607

DO - 10.1109/MNET.011.2000607

M3 - Article

AN - SCOPUS:85104659552

SN - 0890-8044

VL - 35

SP - 286

EP - 294

JO - IEEE Network

JF - IEEE Network

IS - 4

M1 - 9409842

ER -

Collaborative Cross System AI: Toward 5G System and beyond

Abstrakti

Pääsy asiakirjaan

Muut tiedostot ja linkit

Sormenjälki

Projektit

CSN: Customized Software Networking across Multiple Administrative Domains

Siteeraa tätä