Real-time adaptive resource management for high-resolution computer vision over private 5G networks

IF 4.6 2区计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Computer Networks Pub Date : 2025-08-22 DOI:10.1016/j.comnet.2025.111644

Rui Silva, Filipe Antão, David Santos, André Perdigão, Tiago Barros, Fatma Marzouk, Alisson Chaves, Daniel Corujo, Rui L. Aguiar

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Abstract

The advancements in wireless networking technologies empower new opportunities and applications. However, these advanced networks are increasingly consuming more energy to provide higher performance. In line with the United Nations sustainable development goals and the need to reduce networking energy consumption, this paper presents an efficient dynamic slicing and antenna control architecture for 5G networks. The architecture was then applied to a smart port scenario, where a pre-gate is used to control the entrance of trucks into the port with the aid of a camera, with the video stream being analyzed in a datacenter to detect the presence of a truck and access its details. Experimental results showed that the architecture was able to potentially reduce the energy expenditure of the considered scenario in 2.26 MWh in a year, considering a real statistical number of trucks entering the Portuguese Sines Port in 2017. Moreover, it reduced the energy consumption of the User Equipment, computing infrastructure, and wireless network in 9%, 23% and 14% respectively.

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专用5G网络上高分辨率计算机视觉的实时自适应资源管理

无线网络技术的进步带来了新的机遇和应用。然而，为了提供更高的性能，这些先进的网络正在消耗越来越多的能量。根据联合国可持续发展目标和降低网络能耗的需要，本文提出了一种高效的5G网络动态切片和天线控制架构。然后将该架构应用于智能港口场景，在该场景中，通过摄像头使用预闸门来控制卡车进入港口，并在数据中心分析视频流以检测卡车的存在并获取其详细信息。实验结果表明，考虑到2017年进入葡萄牙锡尼什港的卡车的实际统计数量，该架构能够在一年内潜在地减少所考虑场景的能源消耗2.26兆瓦时。此外，它将用户设备、计算基础设施和无线网络的能耗分别降低了9%、23%和14%。

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来源期刊

Computer Networks 工程技术-电信学

CiteScore

10.80

自引率

3.60%

发文量

434

审稿时长

8.6 months

期刊介绍： Computer Networks is an international, archival journal providing a publication vehicle for complete coverage of all topics of interest to those involved in the computer communications networking area. The audience includes researchers, managers and operators of networks as well as designers and implementors. The Editorial Board will consider any material for publication that is of interest to those groups.