VINIA: Voice-Enabled Intent-Based Networking for Industrial Automation
Computer Science and Information Systems, Tome 21 (2024) no. 1
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Intent Based Networking (IBN) is a promising approach for automating and managing large and complex networks. Integrating Voice-enabled Virtual Assistants (VVAs) with IBN and Software Defined Networking (SDN) has improved network management efficiency and flexibility. However, there is still room for optimization improvement in installing intents in industrial scenarios. Network Orchestration Automation plays an important role within the Beyond 5G and 6G Networks, considering existing practices for orchestrating 5G Network Functions. This work presents an extended preliminary architecture for a voice-enabled IBN system called VINIA for industrial network automation. The new approach allows the configuration of more network assets (e.g., 5G networks), leveraging Network Orchestrators and Network Slice Managers, thus improving the system’s capabilities. The results provide insights into this solution’s potential benefits and limitations to enhance the automation of industrial networks’ management and orchestration procedures.
Keywords:
Intent, Intent-driven Management Service, Network Slicing, Industrial Virtual Voice Assistant
@article{CSIS_2024_21_1_a22,
author = {Raul Barbosa and Jo\~ao Fonseca and Marco Ara\'ujo and Daniel Corujo},
title = {VINIA: {Voice-Enabled} {Intent-Based} {Networking} for {Industrial} {Automation}},
journal = {Computer Science and Information Systems},
year = {2024},
volume = {21},
number = {1},
url = {http://geodesic.mathdoc.fr/item/CSIS_2024_21_1_a22/}
}
TY - JOUR AU - Raul Barbosa AU - João Fonseca AU - Marco Araújo AU - Daniel Corujo TI - VINIA: Voice-Enabled Intent-Based Networking for Industrial Automation JO - Computer Science and Information Systems PY - 2024 VL - 21 IS - 1 UR - http://geodesic.mathdoc.fr/item/CSIS_2024_21_1_a22/ ID - CSIS_2024_21_1_a22 ER -
Raul Barbosa; João Fonseca; Marco Araújo; Daniel Corujo. VINIA: Voice-Enabled Intent-Based Networking for Industrial Automation. Computer Science and Information Systems, Tome 21 (2024) no. 1. http://geodesic.mathdoc.fr/item/CSIS_2024_21_1_a22/