Next-Generation Industrial Networks: Integrating Time-Sensitive Networking for Smart Factory Reliability

Abstract

Traditional industrial communication networks may not meet the requirements of the main smart factory applications, such as remote control and safety applications (which can be considered strictly real-time) and augmented reality (which consumes a large bandwidth). This work suggests an enhanced communication network that can serve an optimum case for the smart factory model to include heavy data and real-time applications. The concepts of Time-Sensitive Networks (TSN) are applied to address the limitation of real-time applications, whereas edge computing is used to assimilate the heavy data applications. The current work considers an experimental scenario where the H.265 compression method based on the concept of edge computing was used. This was done to mitigate the impact of the consumed capacity on the performance of the overall network for an augmented reality application. The results of implementing the enhanced communication network indicated that the latency of real-time applications is less than 1 ms, while the packet data delivery rate for rest applications is 99.999%.

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