Technical framework demonstrates application-side traffic shaping alongside network engineering in 5G non-public networks, suggesting improved quality of service for adaptive robotic systems.
Cloud and edge computing, distributed AI, and most recently 5G/6G communications are coming together and changing the way we collaborate, connect and interact. A new generation of AI-powered robots are also expected to be facilitated by these digital technological breakthroughs. Robots are supposed to tackle unknown situations and adapt in the long term by collaborating, connecting and interacting with the digital world. Such applications generate versatile, perpetuated and rapidly changing transmission demands to the network. Traditional network resource management is insufficient in supporting such traffic to meet the QoS. In this paper, we go a step further, in addition to the effort on the network side for traffic engineering; we also work on the application side to shape the traffic within non-public networks. We present an initial development for the proposed intent-based deployment for robotic applications.
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Qiu et al. (2023) studied this question.
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