移动边缘计算在铁路行业的应用

张维真; 石平刚; 任爽

doi:10.3969/j.issn.1005-8451.2024.03.04

移动边缘计算在铁路行业的应用

doi: 10.3969/j.issn.1005-8451.2024.03.04

张维真^{1, 2},
石平刚³,
任爽^1,

1.
北京交通大学　计算机与信息技术学院，北京　100044
2.
中国铁路济南局集团有限公司　济南站，济南　250001
3.
中国铁路济南局集团有限公司　信息技术所，济南　250001

基金项目: 国家自然科学基金资助项目（62072025）

详细信息

作者简介:
张维真，硕士研究生

石平刚，教授级高工

中图分类号: U29 : TP301.6
出版历程
- 收稿日期: 2023-05-10
- 刊出日期: 2024-03-28

Mobile edge computing applied to railway industry

1.
School of Computer and Information Technology, Beijing Jiaotong University, Beijing　100044, China
2.
Jinan Station, China Railway Jinan Group Co. Ltd., Jinan Station, Jinan　250001, China
3.
Information Technology Institute, China Railway Jinan Group Co. Ltd., Jinan　250001, China

摘要

摘要: 为满足智能铁路的快速发展对铁路应用数据大容量传输、计算处理的实时性、安全性提出的更高要求，文章研究移动边缘计算（MEC，Mobile Edge Computing）的相关概念和基本框架，分析其关键技术、应用场景；针对铁路MEC业务需求，总结MEC在智能运营、智能装备、智能建造场景下的应用方案；结合当前存在的问题，展望MEC未来发展的技术趋势，为提升铁路智能化提供助力。
- 智能铁路 /
- 移动边缘计算（MEC） /
- 智能运营 /
- 智能装备 /
- 智能建造
Abstract: In order to meet the higher requirements of the rapid development of intelligent railway for the real-time and security of railway application data mass transmission and computing processing, this paper studied the related concepts and basic framework of Mobile Edge Computing (MEC), and analyzes its key technologies and application scenarios, summarized the application solutions of MEC in intelligent operation, intelligent equipment, and intelligent construction scenarios, targeting the business needs of railway MEC, combined the current problems and looked forward to the technological trends of MEC's future development, provided assistance for improving railway intelligence.
- intelligent railway /
- Mobile Edge Computing (MEC) /
- intelligent operation /
- intelligent equipment /
- intelligent construction

HTML全文

图 1 MEC再基站体系结构

下载: 全尺寸图片幻灯片

图 2 移动边缘计算基本框架

下载: 全尺寸图片幻灯片

图 3 MEC与5G的融合架构

下载: 全尺寸图片幻灯片

图 4 MEC在故障预测的应用

下载: 全尺寸图片幻灯片

图 5 MEC在智能动车组的应用

下载: 全尺寸图片幻灯片

参考文献(33)

[1]	王同军. 中国智能高速铁路2.0的内涵特征、体系架构与实施路径[J]. 铁路计算机应用,2022,31(7):1-9. doi: 10.3969/j.issn.1005-8451.2022.07.01
[2]	Ai B, Molisch A F, Rupp M, et al. 5G key technologies for smart railways[J]. Proceedings of the IEEE, 2020, 108(6): 856-893. doi: 10.1109/JPROC.2020.2988595
[3]	刘佳佳,吴昊,李盼盼. 铁路5G移动通信系统边缘计算安全研究[J]. 计算机工程与应用,2021,57(12):1-10. doi: 10.3778/j.issn.1002-8331.2102-0052
[4]	谷晓会,章国安. 移动边缘计算在车载网中的应用综述[J]. 计算机应用研究,2020,37(6):1615-1621. doi: 10.19734/j.issn.1001-3695.2019.01.0001
[5]	韩晓非,宋青芸,韩瑞寅,等. 移动边缘计算卸载技术综述[J]. 电讯技术,2022,62(9):1368-1376. doi: 10.3969/j.issn.1001-893x.2022.09.025
[6]	李毅,董根才,蔺伟,等. 边缘计算技术在铁路5G移动通信中的应用研究[J]. 中国铁路,2020(11):23-30. doi: 10.19549/j.issn.1001-683x.2020.11.023
[7]	谢人超,廉晓飞,贾庆民,等. 移动边缘计算卸载技术综述[J]. 通信学报,2018,39(11):138-155. doi: 10.11959/j.issn.1000-436x.2018215
[8]	Liu J, Mao Y Y, Zhang J, et al. Delay-optimal computation task scheduling for mobile-edge computing systems[C]//Proceedings of 2016 IEEE International Symposium on Information Theory, 10-15 July, 2016, Barcelona, Spain. New York, USA: IEEE, 2016: 1451-1455.
[9]	Mao Y Y, Zhang J, Letaief K B. Dynamic computation offloading for mobile-edge computing with energy harvesting devices[J]. IEEE Journal on Selected Areas in Communications, 2016, 34(12): 3590-3605. doi: 10.1109/JSAC.2016.2611964
[10]	Jia M K, Cao J N, Yang L. Heuristic offloading of concurrent tasks for computation-intensive applications in mobile cloud computing[C]//Proceedings of 2014 IEEE Conference on Computer Communications Workshops, 27 April, 2014-2 May, 2014, Toronto, ON, Canada. New York, USA: IEEE, 2014: 352-357.
[11]	Kamoun M, Labidi W, Sarkiss M. Joint resource allocation and offloading strategies in cloud enabled cellular networks[C]//Proceedings of 2015 IEEE International Conference on Communications, 8-12 June, 2015, London, UK. New York, USA: IEEE, 2015: 5529-5534.
[12]	Zhang H L, Guo J, Yang L C, et al. Computation offloading considering fronthaul and backhaul in small-cell networks integrated with MEC[C]//Proceedings of 2017 IEEE Conference on Computer Communications Workshops, 1-4 May, 2017, Atlanta, GA, USA. New York, USA: IEEE, 2017: 115-120.
[13]	You C S, Huang K B. Multiuser resource allocation for mobile-edge computation offloading[C]//Proceedings of 2016 IEEE Global Communications Conference, 4-8 December, 2016, Washington, DC, USA. New York, USA: IEEE, 2016: 1-6.
[14]	Muñoz O, Pascual-Iserte A, Vidal J. Optimization of radio and computational resources for energy efficiency in latency-constrained application offloading[J]. IEEE Transactions on Vehicular Technology, 2015, 64(10): 4738-4755. doi: 10.1109/TVT.2014.2372852
[15]	Nan Y C, Li W, Bao W, et al. Adaptive energy-aware computation offloading for cloud of things systems[J]. IEEE Access, 2017 (5): 23947-23957. doi: 10.1109/ACCESS.2017.2766165
[16]	Liu L Q, Chang Z, Guo X J, et al. Multi-objective optimization for computation offloading in mobile-edge computing[C]//Proceedings of 2017 IEEE Symposium on Computers and Communications, 3-6 July, 2017, Heraklion, Greece. New York, USA: IEEE, 2017: 832-837.
[17]	Di Valerio V, Lo Presti F. Optimal Virtual Machines allocation in mobile femto-cloud computing: an MDP approach[C]//Proceedings of 2014 Wireless Communications and Networking Conference Workshops, 6-9 April, 2014, Istanbul, Turkey. New York, USA: IEEE, 2014: 7-11.
[18]	Zhao T C, Zhou S, Guo X Y, et al. A cooperative scheduling scheme of local cloud and internet cloud for delay-aware mobile cloud computing[C]//Proceedings of 2015 IEEE Globecom Workshops, 6-10 December, 2015, San Diego, CA, USA. New York, USA: IEEE, 2015: 1-6.
[19]	Guo X Y, Singh R, Zhao T C, et al. An index based task assignment policy for achieving optimal power-delay tradeoff in edge cloud systems[C]//Proceedings of 2016 IEEE International Conference on Communications, 22-27 May, 2016, Kuala Lumpur, Malaysia. New York, USA: IEEE, 2016: 1-7.
[20]	Wang C M, Yu F R, Liang C C, et al. Joint computation offloading and interference management in wireless cellular networks with mobile edge computing[J]. IEEE Transactions on Vehicular Technology, 2017, 66(8): 7432-7445. doi: 10.1109/TVT.2017.2672701
[21]	Oueis J, Calvanese-Strinati E, De Domenico A, et al. On the impact of backhaul network on distributed cloud computing[C]//Proceedings of 2014 IEEE Wireless Communications and Networking Conference Workshops, 6-9 April, 2014, Istanbul, Turkey. New York, USA: IEEE, 2014: 12-17.
[22]	武继刚,刘同来,李境一,等. 移动边缘计算中的区块链技术研究进展[J]. 计算机工程,2020,46(8):1-13. doi: 10.19678/j.issn.1000-3428.0057749
[23]	Tang W D, Zhao X, Rafique W, et al. A blockchain-based offloading approach in fog computing environment[C]//Proceedings of 2018 IEEE International Conference on Parallel & Distributed Processing with Applications, Ubiquitous Computing & Communications, Big Data & Cloud Computing, Social Computing & Networking, Sustainable Computing & Communications, 11-13 December, 2018, Melbourne, VIC, Australia. New York, USA: IEEE, 2018: 308-315.
[24]	Zhao H W, Zhang Y, Peng Y, et al. Lightweight backup and efficient recovery scheme for health blockchain keys[C]//Proceedings of the 13th International Symposium on Autonomous Decentralized System, 22-24 March, 2017, Bangkok, Thailand. New York, USA: IEEE, 2017: 229-234.
[25]	Zhang L. Key management scheme for secure channel establishment in fog computing[J]. IEEE Transactions on Cloud Computing, 2021, 9(3): 1117-1128. doi: 10.1109/TCC.2019.2903254
[26]	Ma Z F, Wang X C, Jain D K, et al. A blockchain-based trusted data management scheme in edge computing[J]. IEEE Transactions on Industrial Informatics, 2020, 16(3): 2013-2021. doi: 10.1109/TII.2019.2933482
[27]	ETSI. Multi-access edge computing (MEC); phase 2: use cases and requirements: ETSI GS MEC 002 V2.1. 1[S]. ETSI, 2018.
[28]	刘语馨,陈姝,钟章队. 边缘云技术在智能铁路中的应用[J]. 铁道通信信号,2019,55(S1):7-12. doi: 10.13879/j.issn1000-7458.2019-S1.19446
[29]	艾渤,马国玉,钟章队. 智能高铁中的5G技术及应用[J]. 中兴通讯技术,2019,25(6):42-47,54. doi: 10.12142/ZTETJ.201906007
[30]	张心宇,王喆,郭歌,等. 铁路信息系统云边协同体系架构研究[J]. 铁路计算机应用,2022,31(10):1-5.
[31]	葛伟涛. 铁路5G网络边缘计算技术研究[J]. 铁路通信信号工程技术,2023,20(2):33-36,67. doi: 10.3969/j.issn.1673-4440.2023.02.007
[32]	郜城城,周旭,范鹏飞,等. 移动边缘计算技术在高铁通信网络中的应用[J]. 计算机系统应用,2018,27(8):56-62. doi: 10.15888/j.cnki.csa.006507
[33]	杨兴磊,鲁玉龙,张俊尧,等. 基于边缘计算的智慧铁路工地生产管理系统[J]. 铁路计算机应用,2020,29(10):26-29. doi: 10.3969/j.issn.1005-8451.2020.10.006