Slicing enabled 5G experimentation platform for the Robotics vertical industry
Suvidha Mhatre, Kostantinos Ramantas, Renxi Qiu, Christos Verikoukis
- Year
- 2021
- Citations
- 3
Abstract
This paper will discuss a network slicing 5G architecture and framework to enable efficient robotics operation, while improving Quality of Service (QoS). Furthermore, it will focus on a user-centric paradigm of integrating vertical knowledge into the existing 5G solutions. The software architecture and test- bed includes open air Interface (OAI) and open source MANO (OSM) based 5G testing platform to provide wireless connectivity to robots. It targets on minimising developers need for the comprehension of 5G when developing vertical applications of autonomous robotic systems. Different types of slicing framework considerations, edge computing aspects and orchestration options are evaluated as part of the architecture. The work is carried out by analysing various 5G architecture especially the potentials of relevant work already launched under 5GPPP Phases, 3GPP and ETSI, as well as by studying key robotic workflows of verticals sectors.
Keywords
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