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A Joint Scheduling Scheme for WiFi Access TSN. | LitMetric

A Joint Scheduling Scheme for WiFi Access TSN.

Sensors (Basel)

School of Electronic Information, Wuhan University, Wuhan 430072, China.

Published: April 2024

AI Article Synopsis

  • * Time-sensitive networking (TSN) is emerging as a key Ethernet tech for reliable industrial communication, while Wi-Fi offers high mobility and ease of access for users.
  • * This paper addresses the scheduling challenge in networks combining TSN and Wi-Fi, introducing a greedy strategy distributed estimation (GE) algorithm that outperforms traditional methods in adaptability and efficiency, especially under high traffic.

Article Abstract

In the context of Industry 4.0, industrial production equipment needs to communicate through the industrial internet to improve the intelligence of industrial production. This requires the current communication network to have the ability of large-scale equipment access, multiple communication protocols/heterogeneous systems interoperability, and end-to-end deterministic low-latency transmission. Time-sensitive network (TSN), as a new generation of deterministic Ethernet communication technology, is the main development direction of time-critical communication technology applied in industrial environments, and Wi-Fi technology has become the main way of wireless access for users due to its advantages of high portability and mobility. Therefore, accessing WiFi in the TSN is a major development direction of the current industrial internet. In this paper, we model the scheduling problem of TSN and WiFi converged networks and propose a scheme based on a greedy strategy distributed estimation algorithm (GE) to solve the scheduling problem. Compared with the integer linear programming (ILP) algorithm and the Tabu algorithm, the algorithm implemented in this paper outperforms the other algorithms in being able to adapt to a variety of different scenarios and in scheduling optimization efficiency, especially when the amount of traffic to be deployed is large.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11053665PMC
http://dx.doi.org/10.3390/s24082554DOI Listing

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