计算机科学
计算机网络
实时计算
电气工程
工程类
电信
作者
Yu Chen,Shi Guo,Mohammad Al-Quraan,Yusuf Sambo,Oluwakayode Onireti,Muhammad Ali Imran
出处
期刊:IEEE Transactions on Vehicular Technology
[Institute of Electrical and Electronics Engineers]
日期:2024-02-01
卷期号:73 (6): 8903-8914
被引量:6
标识
DOI:10.1109/tvt.2024.3361160
摘要
Monitoring of trackside weather is a critical aspect of railway operations, mainly for safety and efficiency reasons. Unfortunately, current cellular networks, including the fourth-generation and fifth-generation (5G) cellular networks, do not provide ubiquitous coverage for rail lines mainly due to an unfavorable cost-benefit realization. In this paper, we propose a Long Range (LoRa) mesh-5G integrated network that tackles this problem by utilizing a 5G network for backhaul, computing and storage, and LoRa mesh to extend coverage. We design a LoRa mesh server that runs on a private cloud of the 5G network to manage the LoRa mesh network. We integrate edge computing into the network and design a cloud-edge-terminal collaborative architecture with three algorithms for timely significant-change updates, packet loss detection, and adaptive thresholds to reduce the packet rate and data volume of the network. We validate the design by implementing a proof-of-concept on the 5G testbed at the University of Glasgow. The experimental results demonstrate the feasibility of the network and the cloud-edge-terminal collaborative architecture.
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