工业物联网数据采集网络的信息年龄研究

doi:10.16088/j.issn.1001-6600.2024061104

摘要/Abstract

摘要： 针对工业物联网数据采集系统对高时效性和高可靠性的需求,考虑不同优先级流量的共存、资源的稀缺性以及信道的随机性,本文提出一种基于随机混合系统的方法,构建适用于此类网络的时效性表征模型。该模型旨在刻画存在大量优先级各异流量的条件下,数据采集网络的时效性特征,并探讨系统中各耦合参数对信息时效性的影响。研究结果表明,通过优化链路感知策略可有效减少传输错误概率对信息年龄的负面影响。在相同优先级网络环境中,链路的信息年龄随着数据生成速率的增加而逐渐趋向稳定极限值;而在不同优先级的网络中,较高优先级链路通过牺牲其他链路的时效性,提升了自身时效性。随着数据生成速率的增加,系统逐渐呈现退化为单链路模式的趋势。因此,为保障系统的整体时效性,需要通过优化低优先级链路的感知资源分配来确保系统的高效运行。

关键词: 信息年龄, 工业物联网, 数据采集, 优先级, 感知资源分配, 随机混合系统

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

中图分类号: TN929.5; TP393

曹杰, 江红兵, 朱旭. 工业物联网数据采集网络的信息年龄研究[J]. 广西师范大学学报（自然科学版）, 2025, 43(5): 75-90.

CAO Jie, JIANG Hongbing, ZHU Xu. Research on Age of Information in Data Collection Networks for Industrial Internet of Things[J]. Journal of Guangxi Normal University(Natural Science Edition), 2025, 43(5): 75-90.

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