The SYRROCA AI-empowered network automation platform

Authors :: Jose Manuel Sanchez Vilchez
Alessio Diamanti
Stefano Secci
Orange Labs
Centre d'études et de recherche en informatique et communications (CEDRIC)
Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM)
Source :: 2021 24th Conference on Innovation in Clouds, Internet and Networks and Workshops (ICIN), 2021 24th Conference on Innovation in Clouds, Internet and Networks and Workshops (ICIN), Mar 2021, Paris, France. pp.140-142, ⟨10.1109/ICIN51074.2021.9385535⟩, ICIN
Publication Year :: 2021
Publisher :: HAL CCSD, 2021.
Abstract: This paper synthetically presents the SYRROCA (SYstem Radiography and ROot Cause Analysis) network automation framework at the state of the art, and details its experimental platform sufficiently enough to understand its technical demonstration. The framework aims to learn nominal operating conditions of a softwarized network service and characterize anomalies in real-time, while offering a compact system state representation called radiography. This representation can provide to operational teams with a real-time insight on anomalies at physical and virtualized layers. The related technical demonstration showcases how SYRROCA can detect real-time anomalies of different nature on a containerized vIMS (virtual IP Multimedia Subsystem) service managed by Kubernetes.

Language :: English
Database :: OpenAIRE
Journal :: 2021 24th Conference on Innovation in Clouds, Internet and Networks and Workshops (ICIN), 2021 24th Conference on Innovation in Clouds, Internet and Networks and Workshops (ICIN), Mar 2021, Paris, France. pp.140-142, ⟨10.1109/ICIN51074.2021.9385535⟩, ICIN
Accession number :: edsair.doi.dedup.....07d80823ceef2223fde6e1d3d9bc16bc
Full Text :: https://doi.org/10.1109/ICIN51074.2021.9385535⟩