RT Conference Proceedings
T1 Demo: AIML-as-a-service for SLA management of a digital twin virtual network service
A1 Baranda, Jorge
A1 Zeydan, Engin
A1 Casetti, C.
A1 Chiasserini, C. F.
A1 Malinverno, Marco
A1 Puligheddu, C.
A1 Groshev, Milan
A1 Magalhaes Guimaraes, Carlos Eduardo
A1 Tomakh, K.
A1 Kucherenko, D.
A1 Kolodiaznhyi, O.
A1 Mangues-Bafalluy, Josep
AB This demonstration presents an AI/ML platform that is offered as a service (AIMLaaS) and integrated in the management and orchestration (MANO) workflow defined in the project 5Growth following the recommendations of various standardization organizations. In such a system, SLA management decisions (scaling, in this demo) are taken at runtime by AI/ML models that are requested and downloaded by the MANO stack from the AI/ML platform at instantiation time, according to the service definition. Relevant metrics to be injected into the model are also automatically configured so that they are collected, ingested, and consumed along the deployed data engineering pipeline. The use case to which it is applied is a digital twin service, whose control and motion planning function has stringent latency constraints (directly linked to its CPU consumption), eventually determining the need for scaling out/in to fulfill the SLA.
PB IEEE
SN 978-1-6654-0443-3
YR 2021
FD 2021-05-10
LK http://hdl.handle.net/10016/33710
UL http://hdl.handle.net/10016/33710
LA eng
NO Proceedings of: IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS).
NO Work supported in part by EU Commission H2020 5Growth project (Grant No. 856709) and H2020 Europe/Taiwan 5G-Dive project (Grant No. 859881).
DS e-Archivo
RD 28 abr. 2024