Journal of Guangxi Normal University(Natural Science Edition) ›› 2025, Vol. 43 ›› Issue (5): 75-90.doi: 10.16088/j.issn.1001-6600.2024061104

• Physics and Electronic Engineering • Previous Articles     Next Articles

Research on Age of Information in Data Collection Networks for Industrial Internet of Things

CAO Jie1,2, JIANG Hongbing1, ZHU Xu1,2*   

  1. 1. School of Electronic and Information Engineering, Harbin Institute of Technology, Shenzhen Guangdong 518055, China;
    2. Guangxi Key Laboratory of Brain-inspired Computing and Intelligent Chips (Guangxi Normal University), Guilin Guangxi 541004, China
  • Received:2024-06-11 Revised:2025-01-05 Online:2025-09-05 Published:2025-08-05

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Abstract: This paper addresses the need for high timeliness and reliability in industrial Internet of things (IIoT) data acquisition systems. It considers the coexistence of traffic with different priority levels, the scarcity of resources, and the randomness of channels. A method based on a stochastic hybrid system is proposed to construct a timeliness characterization model suitable for such networks. The model is designed to describe the timeliness features of data acquisition networks under conditions involving a large volume of traffic with varying priorities. Based on this model, the paper explores the impact of coupling parameters within the system on the information timeliness. The research results indicate that by optimizing the link sensing strategy, the negative impact of transmission error probability on information age can be effectively reduced. In networks with the same priority, the information age of the link gradually stabilizes towards a limiting value as the data generation rate increases. In networks with different priorities, higher-priority links improve their timeliness by sacrificing the timeliness of other links. As the data generation rate increases, the system gradually trends towards a degradation into a single-link mode. Therefore, to ensure the overall timeliness of the system, it is necessary to optimize the sensing resource allocation for low-priority links to maintain efficient system operation.

Key words: age of information, industrial Internet of things (IIoT), data collection, priority, sensing resource allocation, stochastic hybrid system

CLC Number:  TN929.5; TP393
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