Implementation and Evaluation of 5G MEC-Enabled Smart Factory

Author:

Rekoputra Nadhif Muhammad1,Tseng Chia-Wei1,Wang Jui-Tang1ORCID,Liang Shu-Hao2ORCID,Cheng Ray-Guang1ORCID,Li Yueh-Feng3,Yang Wen-Hao3

Affiliation:

1. Department of Electronic and Computer Engineering, National Taiwan University of Science and Technology, Taipei City 106335, Taiwan

2. Graduate Institute of Intelligent Manufacturing Technology, National Taiwan University of Science and Technology, Taipei City 106335, Taiwan

3. Wireless Communication Laboratory, Telecommunication Laboratory of Chunghwa Telecom, Taipei City 106335, Taiwan

Abstract

A 5G network can provide more comprehensive bandwidth connectivity for the industry 4.0 environment, which requires faster and tremendous data transmission. This study demonstrates the 5G network performance evaluation with MEC, without MEC, WiFi 6, and Ethernet networks. Usually, a 5G network engages with Multi-access Edge Computing, providing the computing functions dedicated to the users on edge nodes. The MEC network architecture presents significant facilities, a network schematic, and data transmission routers. The field test performs high-definition streaming video and heavy-traffic load testing to evaluate the performance based on different protocols by comparing throughput, latency, jitter, and packet loss rate. MEC network performance, streaming video performance, and load test evaluation results reveal that the 5G network working with MEC achieved better performance than when it was working without MEC. The MEC can improve data transmission efficiency by dedicated configuration but is only accessible with authentication from mobile network operators (MNOs). Therefore, MNOs should offer industrial private network users partial authentication for accessing MEC functionality to improve network feasibility and efficiency. In conclusion, this work illustrates the 5G network implementation and performance measurement for constructing a smart factory.

Funder

National Science and Technology Council (NSTC), Taiwan

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering

Reference21 articles.

1. Statista (2022, October 03). Forecast Number of 5G Mobile Subscriptions Worldwide 2019–2026. Available online: https://www.statista.com/statistics/760275/5g-mobile-subscriptions-worldwide/.

2. Cisco (2021, May 05). Cisco Annual Internet Report (2018–2023). Available online: https://www.cisco.com/c/en/us/solutions/collateral/executive-perspectives/annual-internet-report/white-paper-c1-741490.html.

3. Kitanov, S., and Janevski, T. (2014, January 27). State of the Art: Mobile Cloud Computing. Proceedings of the 2014 Sixth International Conference on Computational Intelligence, Communication Systems, and Networks, Tetova, North Macedonia.

4. An open ecosystem for mobile-cloud convergence;Satyanarayanan;IEEE Commun. Mag.,2015

5. Ramirez, R., Huang, C.-Y., and Liang, S.-H. (2022). 5G Digital Twin: A Study of Enabling Technologies. Appl. Sci., 12.

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3