Volume 22 Issue 2
Apr.  2022
Turn off MathJax
Article Contents
DONG Ping, YIN Chen-yang, ZHANG Yu-yang, ZHANG Hong-ke. Review on development of heterogeneous smart cooperative vehicular networks in rail transit[J]. Journal of Traffic and Transportation Engineering, 2022, 22(2): 41-58. doi: 10.19818/j.cnki.1671-1637.2022.02.003
Citation: DONG Ping, YIN Chen-yang, ZHANG Yu-yang, ZHANG Hong-ke. Review on development of heterogeneous smart cooperative vehicular networks in rail transit[J]. Journal of Traffic and Transportation Engineering, 2022, 22(2): 41-58. doi: 10.19818/j.cnki.1671-1637.2022.02.003

Review on development of heterogeneous smart cooperative vehicular networks in rail transit

doi: 10.19818/j.cnki.1671-1637.2022.02.003
Funds:

National Key Research and Development Program of China 2018YFB1800305

National Natural Science Foundation of China 61872029

National Natural Science Foundation of China 61972026

More Information
  • Author Bio:

    DONG Ping(1979-), male, professor, PhD, pdong@bjtu.edu.cn

    YIN Chen-yang(1995-), male, doctoral student, 17111009@bjtu.edu.cn

  • Received Date: 2021-09-28
  • Publish Date: 2022-04-25
  • The research status of vehicular networks of rail transit both at home and abroad was analyzed from three aspects, i.e., cellular wireless access technology, non-cellular wireless access technology, and heterogeneous smart cooperative vehicular network access technology. Considering the problems of non-cellular and cellular wireless access technology, the advantages of cooperatively using heterogeneous wireless resources around rail transit for network convergence and cooperative communications were expounded. The convergence schemes of heterogeneous smart cooperative vehicular networks were discussed from the aspects of the network model and network architecture. In view of the business requirements of intelligent rail transit, the existing research on heterogeneous smart cooperative vehicular networks was systematically classified from the perspectives of reliability and resource utilization. The future development trends of heterogeneous smart cooperative vehicular networks were proposed regarding artificial intelligence, security, and cloud-edge combination. Research results show that the reliability of heterogeneous smart cooperative vehicular networks is comprised of network architecture reliability and data transmission reliability. The former mainly proposes improving reliability in the ways of redundant network architecture, vehicle-to-cloud transmission architecture, software-defined network architecture, and smart and cooperative network architecture. The latter focuses on reducing the packet loss rate in the process of transmission through three ways, i.e., multi-path transmission, network coding, and handoff algorithms. The resource utilization of heterogeneous smart cooperative vehicular networks can be divided into wireless access resource utilization and link scheduling resource utilization. The former improves the throughput and resource utilization by three methods, i.e., channel state prediction, spectrum division, and frequency shift compensation. The latter reduces the influence of heterogeneous links on data transmission and the times of data retransmission and raises the utilization of network resources mainly by scheduling algorithm, receiving and buffer algorithm, and congestion control algorithm. 6 tabs, 7 figs, 79 refs.

     

  • loading
  • [1]
    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. https://www.cnki.com.cn/Article/CJFDTOTAL-ZXTX201906008.htm

    AI Bo, MA Guo-yu, ZHONG Zhang-dui. 5G technologies and applications in high-speed railway[J]. ZTE Technology Journal, 2019, 25(6): 42-47, 54. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-ZXTX201906008.htm
    [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]
    AI B, GUAN K, RUPP M, et al. Future railway services-oriented mobile communications network[J]. IEEE Communications Magazine, 2015, 53(10): 78-85. doi: 10.1109/MCOM.2015.7295467
    [4]
    IBRAHIM E A, BADRAN E F, RIZK M R M. An optimized LTE measurement handover procedure for high speed trains using WINNER Ⅱ channel model[C]//IEEE. 22nd Asia-Pacific Conference on Communications. New York: IEEE, 2016: 197-203.
    [5]
    FOKUM D T, FROST V S. A survey on methods for broadband Internet access on trains[J]. IEEE Communications Surveys and Tutorials, 2010, 12(2): 171-185. doi: 10.1109/SURV.2010.021110.00060
    [6]
    GHANNOUM H, SANZ D. Internet onboard: technical analysis[C]//Springer. 5th International Workshop on Communication Technologies for Vehicles. Berlin: Springer, 2013: 22-30.
    [7]
    BANERJEE S, HEMPEL M, SHARIF H. A survey of wireless communication technologies and their performance for high speed railways[J]. Journal of Transportation Technologies, 2016, 6(1): 15-29. doi: 10.4236/jtts.2016.61003
    [8]
    SCALISE S, MURA R, MIGNONE V. Air interfaces for satellite based digital TV broadcasting in the railway environment[J]. IEEE Transactions on Broadcasting, 2006, 52(2): 158-166. doi: 10.1109/TBC.2006.872991
    [9]
    HO D H, VALAEE S. Information raining and optimal link-layer design for mobile hotspots[J]. IEEE Transactions on Mobile Computing, 2005, 4(3): 271-284. doi: 10.1109/TMC.2005.42
    [10]
    TES T. Study of high-speed wireless data transmissions for railroad operation[R]. Washington DC: Federal Railroad Administration, 2007.
    [11]
    ZHOU T, SHARIF H, HEMPEL M, et al. A quantitative study of mobility impact for real-time services on a Wi-Fi multi-hop network[C]//IEEE. 2008 IEEE 67th Vehicular Technology Conference. New York: IEEE, 2008: 2577-2581.
    [12]
    YAMADA K, SAKAI Y, SUZUKI T, et al. A communication system with a fast handover under a high speed mobile environment[C]//IEEE. 2010 IEEE 72nd Vehicular Technology Conference. New York: IEEE, 2010: 1-5.
    [13]
    ZHAO Ya-wei, WU Yu, FENG Ya-xiong, et al. Dynamic channel selections and performance analysis for high-speed train WiFi network[C]//IEEE. 2015 International Workshop on High Mobility Wireless Communications. New York: IEEE, 2015: 31-35.
    [14]
    SEN A, SIVALINGAM K M, NARAYANAN B K J. Persistent WiFi connectivity during train journey: an SDN based approach[C]//IEEE. 2019 IFIP/IEEE Symposium on Integrated Network and Service Management. New York: IEEE, 2019: 634-638.
    [15]
    OUARZAZI B, BERBINEAU M, DAYOUB I, et al. Channel estimation of OFDM system for high data rate communications on mobile environments[C]//IEEE. 2009 9th International Conference on Intelligent Transport Systems Telecommunications, New York: IEEE, 2009: 425-429.
    [16]
    YEH C H, CHOW C W, LIU Y L, et al. Theory and technology for standard WiMAX over fiber in high speed train systems[J]. Journal of Lightwave Technology, 2010, 28(16): 2327-2336. doi: 10.1109/JLT.2010.2044018
    [17]
    DUDOYER S, DENIAU V, ADRIANO R, et al. Study of the susceptibility of the GSM-R communications face to the electromagnetic interferences of the rail environment[J]. IEEE Transactions on Electromagnetic Compatibility, 2012, 54(3): 667-676. doi: 10.1109/TEMC.2011.2169677
    [18]
    DUDOYER S, DENIAU V, AMBELLOUIS S, et al. Classification of transient EM noises depending on their effect on the quality of GSM-R reception[J]. IEEE Transactions on Electromagnetic Compatibility, 2013, 55(5): 867-874. doi: 10.1109/TEMC.2013.2239998
    [19]
    HASSAN K, GAUTIER R, DAYOUB I, et al. Multiple-antenna-based blind spectrum sensing in the presence of impulsive noise[J]. IEEE Transactions on Vehicular Technology, 2014, 63(5): 2248-2257. doi: 10.1109/TVT.2013.2290839
    [20]
    HE Rui-si, ZHONG Zhang-dui, AI Bo, et al. Shadow fading correlation in high-speed railway environments[J]. IEEE Transactions on Vehicular Technology, 2015, 64(7): 2762-2772.
    [21]
    HE Rui-si, ZHONG Zhang-dui, AI Bo, et al. Measurement- based auto-correlation model of shadow fading for the high-speed railways in urban, suburban, and rural environments[C]// IEEE. 2014 IEEE Antennas and Propagation Society, AP-S International Symposium. New York: IEEE, 2014: 949-950.
    [22]
    SUN Teng-yu, ZHOU Ke-hui, LUO Xiang-hua, et al. Research on the fast handover algorithms of GSM-R for high-speed railway[C]//IEEE. Proceedings-2015 International Conference on Network and Information Systems for Computers. New York: IEEE, 2015: 213-218.
    [23]
    SONG Ya-li, WEN Ying-hong, ZHANG Dan, et al. Fast prediction model of coupling coefficient between pantograph arcing and GSM-R antenna[J]. IEEE Transactions on Vehicular Technology, 2020, 69(10): 11612-11618. doi: 10.1109/TVT.2020.3015057
    [24]
    CALLE-SÁNCHEZ J, MOLINA-GARCÍA M, ALONSO J I, et al. Long term evolution in high speed railway environments: Feasibility and challenges[J]. Bell Labs Technical Journal, 2013, 18(2): 237-253. doi: 10.1002/bltj.21615
    [25]
    ZHOU Yi-qing. Radio environment map based maximum a posteriori Doppler shift estimation for LTE-R[C]//IEEE. 2014 International Workshop on High Mobility Wireless Communications. New York: IEEE, 2014: 7000241.
    [26]
    SNIADY A, SOLER J. LTE for railways: impact on performance of ETCS railway signaling[J]. IEEE Vehicular Technology Magazine, 2014, 9(2): 69-77. doi: 10.1109/MVT.2014.2310572
    [27]
    CALLE-SÁNCHEZ J, MARTINEZ-DE-RIOJA E, MOLINA-GARCIA M, et al. Performance of LTE mobile relay node usage for uplink access in high speed railway scenarios[C]//IEEE. 2015 IEEE Vehicular Technology Conference. New York: IEEE, 2015: 7146012.
    [28]
    IBRAHIM E A, BADRAN E F, RIZK M R M. A power-distance based handover triggering algorithm for LTE-R using WINNERⅡ-D2a channel model[C]//IEEE. 22nd Asia-Pacific Conference on Communications. New York: IEEE, 2016: 167-173.
    [29]
    AHMAD I, CHEN W, CHANG K. LTE-railway user priority-based cooperative resource allocation schemes for coexisting public safety and railway networks[J]. IEEE Access, 2017, 5: 7985-8000. doi: 10.1109/ACCESS.2017.2698098
    [30]
    GUPTA N, SINGH B. A novel seamless handover scheme for high-speed railway transport using dual-antenna system[C]// IEEE. 2019 4th IEEE International Conference on Recent Trends on Electronics, Information, Communication and Technology. New York: IEEE, 2019: 1160-1165.
    [31]
    HE Rui-si, AI Bo, WANG Gong-pu, et al. High-speed railway communications: from GSM-R to LTE-R[J]. IEEE Vehicular Technology Magazine, 2016, 11(3): 49-58. doi: 10.1109/MVT.2016.2564446
    [32]
    HE Rui-si, ZHONG Zhang-dui, AI Bo, et al. Reducing the cost of high-speed railway communications: from the propagation channel view[J]. IEEE Transactions on Intelligent Transportation Systems, 2015, 16(4): 2050-2060. doi: 10.1109/TITS.2015.2390614
    [33]
    KIM Y, LEE H Y, HWANG P, et al. Feasibility of mobile cellular communications at millimeter wave frequency[J]. IEEE Journal of Selected Topics in Signal Processing, 2016, 10(3): 589-599. doi: 10.1109/JSTSP.2016.2520901
    [34]
    HE Dang-ping, AI Bo, GUAN Ke, et al. Channel measurement, simulation, and analysis for high-speed railway communications in 5G millimeter-wave band[J]. IEEE Transactions on Intelligent Transportation Systems, 2018, 19(10): 3144-3158. doi: 10.1109/TITS.2017.2771559
    [35]
    ZHOU Tao, LI Hua-yu, WANG Yang, et al. Channel modeling for future high-speed railway communication systems: a survey[J]. IEEE Access, 2019, 7: 52818-52826. doi: 10.1109/ACCESS.2019.2912408
    [36]
    SHENG Jie, TANG Zi-wen, WU Cheng, et al. Game theory-based multi-objective optimization interference alignment algorithm for HSR 5G heterogeneous ultra-dense network[J]. IEEE Transactions on Vehicular Technology, 2020, 69(11): 13371-13382. doi: 10.1109/TVT.2020.3025778
    [37]
    FENG Bo-hao, ZHANG Hong-ke, ZHOU Hua-chun, et al. Locator/identifier split networking: a promising future internet architecture[J]. IEEE Communications Surveys and Tutorials, 2017, 19(4): 2927-2948. doi: 10.1109/COMST.2017.2728478
    [38]
    ZHANG Hong-ke, QUAN Wei, CHAO Han-chieh, et al. Smart identifier network: a collaborative architecture for the future internet[J]. IEEE Network, 2016, 30(3): 46-51. doi: 10.1109/MNET.2016.7474343
    [39]
    HAN M, HAN K S, LEE D J. Fast IP handover performance improvements using performance enhancing proxys between satellite networks and wireless LAN networks for high-speed trains[C]//IEEE. 2008 IEEE Vehicular Technology Conference. New York: IEEE, 2008: 2341-2344.
    [40]
    TERADA M, TERAOKA F. Providing a high-speed train with a broadband and fault tolerant IPv4/6 NEMO environment[C]//IEEE. 2012 IEEE Globecom Workshops. New York: IEEE, 2012: 1052-1056.
    [41]
    LIU Yi-wei, NERI A, RUGGERI A, et al. A MPTCP-based network architecture for intelligent train control and traffic management operations[J]. IEEE Transactions on Intelligent Transportation Systems, 2017, 18(9): 2290-2302. doi: 10.1109/TITS.2016.2633531
    [42]
    HU Yun, CHANG Zheng, LI Hong-yan, et al. Service provisioning and user association for heterogeneous wireless railway networks[J]. IEEE Transactions on Communications, 2017, 65(7): 3066-3078. doi: 10.1109/TCOMM.2017.2687930
    [43]
    HU Yun, LI Hong-yan, CHANG Zheng, et al. Scheduling strategy for multimedia heterogeneous high-speed train networks[J]. IEEE Transactions on Vehicular Technology, 2017, 66(4): 3265-3279. doi: 10.1109/TVT.2016.2587080
    [44]
    MAZZENGA F, GIULIANO R, NERI A, et al. Integrated public mobile radio networks/satellite for future railway communications[J]. IEEE Wireless Communications, 2017, 24(2): 90-97. doi: 10.1109/MWC.2016.1500266WC
    [45]
    YAN Xiao-yun, DONG Ping, DU Xiao-jiang, et al. Congestion game with link failures for network selection in high-speed vehicular networks[J]. IEEE Access, 2018, 6: 76165-76175. doi: 10.1109/ACCESS.2018.2884766
    [46]
    WU Yong-dong, YE Deng-pan, WEI Zhuo, et al. Situation-aware authenticated video broadcasting over train-trackside WiFi networks[J]. IEEE Internet of Things Journal, 2019, 6(2): 1617-1627. doi: 10.1109/JIOT.2018.2859185
    [47]
    CHEN Ya-li, AI Bo, NIU Yong, et al. Resource allocation for device-to-device communications in multi-cell multi-band heterogeneous cellular networks[J]. IEEE Transactions on Vehicular Technology, 2019, 68(5): 4760-4773. doi: 10.1109/TVT.2019.2903858
    [48]
    ZHANG Xiao-ya, DONG Ping, DU Xiao-jiang, et al. Space-ground integrated information network enabled Internet of vehicles: architecture and key mechanisms[J]. IEEE Communications Standards Magazine, 2020, 4(4): 11-17. doi: 10.1109/MCOMSTD.001.2000015
    [49]
    WANG Xin-mu, LI He-wu, YAO Wen-bing, et al. Content delivery for high-speed railway via integrated terrestrial-satellite networks[C]//IEEE. 2020 IEEE Wireless Communications and Networking Conference. New York: IEEE, 2020: 9120643.
    [50]
    LIU Bin, NI Wei, LIU Ren-ping, et al. Optimal selection of heterogeneous network interfaces for high-speed rail communications[J]. IEEE Transactions on Vehicular Technology, 2020, 69(12): 15005-15018. doi: 10.1109/TVT.2020.3031923
    [51]
    YAN Li, FANG Xu-ming, HAO Li, et al. Safety-oriented resource allocation for space-ground integrated cloud networks of high-speed railways[J]. IEEE Journal on Selected Areas in Communications, 2020, 38(12): 2747-2759. doi: 10.1109/JSAC.2020.3005487
    [52]
    XUN Ding, XIN Chen, JIANG Wen-yi. The analysis of GSM-R redundant network and reliability models on high-speed railway[C]//IEEE. 2010 International Conference on Electronics and Information Engineering. New York: IEEE, 2010: V2154-V2158.
    [53]
    LUO Qing-lin, FANG Wei, WU Jin-song, et al. Reliable broadband wireless communication for high speed trains using baseband cloud[J]. EURASIP Journal on Wireless Communications and Networking, 2012, 2012: 1-12. doi: 10.1186/1687-1499-2012-1
    [54]
    DONG Ping, ZHENG Tao, DU Xiao-jiang, et al. SVCC-HSR: providing secure vehicular cloud computing for intelligent high-speed rail[J]. IEEE Network, 2018, 32(3): 64-71. doi: 10.1109/MNET.2018.1700330
    [55]
    YASEEN F A, AL-RAWESHIDY H S. Proactive forwarding of high data rate in smart virtualization networks for high-speed trains[J]. IEEE Systems Journal, 2019, 14(2): 1670-1681.
    [56]
    张宏科, 罗洪斌. 智慧协同网络体系基础研究[J]. 电子学报, 2013, 41(7): 1249-1252, 1254. doi: 10.3969/j.issn.0372-2112.2013.07.001

    ZHANG Hong-ke, LUO Hong-bin. Fundamental research on theories of smart and cooperative networks[J]. Acta Electronica Sinica, 2013, 41(7): 1249-1252, 1254. (in Chinese) doi: 10.3969/j.issn.0372-2112.2013.07.001
    [57]
    ZHANG Yu-yang, DONG Ping, DU Xiao-jiang, et al. BNNC: improving performance of multipath transmission in heterogeneous vehicular networks[J]. IEEE Access, 2019, 7: 158113-158125. doi: 10.1109/ACCESS.2019.2948954
    [58]
    LOPEZ I, AGUADO M, PINEDO C, et al. SCADA systems in the railway domain: enhancing reliability through redundant multipath TCP[C]//IEEE. 2015 IEEE Conference on Intelligent Transportation Systems. New York: IEEE, 2015: 2305-2310.
    [59]
    XU Chang-qiao, LI Zhuo-feng, ZHONG Lu-jie, et al. CMT-NC: improving the concurrent multipath transfer performance using network coding in wireless networks[J]. IEEE Transactions on Vehicular Technology, 2016, 65(3): 1735-1751. doi: 10.1109/TVT.2015.2409556
    [60]
    XU Chang-qiao, WANG Peng, XIONG Chun-shan, et al. Pipeline network coding-based multipath data transfer in heterogeneous wireless networks[J]. IEEE Transactions on Broadcasting, 2017, 63(2): 376-390. doi: 10.1109/TBC.2016.2590819
    [61]
    MA Bin, WANG Dong, CHENG Shuang-guo, et al. Modeling and analysis for vertical handoff based on the decision tree in a heterogeneous vehicle network[J]. IEEE Access, 2017, 5: 8812-8824. doi: 10.1109/ACCESS.2017.2707801
    [62]
    YANG Yu-wen, GAO Fei-fei, ZHONG Zhi-meng, et al. Deep transfer learning-based downlink channel prediction for FDD massive MIMO systems[J]. IEEE Transactions on Communications, 2020, 68(12): 7485-7497. doi: 10.1109/TCOMM.2020.3019077
    [63]
    WANG Cheng, WU Qing-ting, TANG Zi-wen, et al. Spectrum management in high-speed railway cooperative cognitive radio network based on multi-agent reinforcement learning[C]//IEEE. 16th IEEE International Wireless Communications and Mobile Computing Conference. New York: IEEE, 2020: 702-707.
    [64]
    王增浩, 杨丽花, 程露, 等. 5G高速移动系统中基于BP神经网络的多普勒频偏估计方法[J]. 电信科学, 2020, 36(4): 83-90. https://www.cnki.com.cn/Article/CJFDTOTAL-DXKX202004011.htm

    WANG Zeng-hao, YANG Li-hua, CHENG Lu, et al. BP neural network based Doppler frequency offset estimation method for 5G high-speed mobile system[J]. Telecommunications Science, 2020, 36(4): 83-90. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-DXKX202004011.htm
    [65]
    NIKA A, ZHU Yi-bo, DING Ning, et al. Energy and performance of smartphone radio bundling in outdoor environments[C]//ACM. Proceedings of the 24th International Conference on World Wide Web. New York: ACM, 2015: 809-819.
    [66]
    SCHARF M, KIESEL S. NXG03-5: head-of-line blocking in TCP and SCTP: analysis and measurements[C]//IEEE. 2006 Global Telecommunications Conference. New York: IEEE, 2006: 1-5.
    [67]
    PAASCH C, FERLIN S, ALAY O, et al. Experimental evaluation of multipath TCP schedulers[C]//ACM. ACM SIGCOMM 2014 Capacity Sharing Workshop. New York: ACM, 2014: 27-32.
    [68]
    PAASCH C, DETAL G, DUCHENE F, et al. Exploring mobile/WiFi handover with multipath TCP[C]//ACM. 2012 ACM SIGCOMM Workshop on Cellular Networks: Operations, Challenges, and Future Design. New York: ACM, 2012: 31-36.
    [69]
    FERLIN S, ALAY Ö, MEHANI O, et al. BLEST: Blocking estimation-based MPTCP scheduler for heterogeneous networks[C]//IEEE. 2016 IFIP Networking Conference (IFIP Networking) and Workshops. New York: IEEE, 2016: 431-439.
    [70]
    GARCIA-SAAVEDRA A, KARZAND M, LEITH D J. Low delay random linear coding and scheduling over multiple interfaces[J]. IEEE Transactions on Mobile Computing, 2017, 16(11): 3100-3114. doi: 10.1109/TMC.2017.2686379
    [71]
    ZHANG Yu-yang, DONG Ping, DU Xiao-jiang, et al. Dynamic time-threshold based receive buffer for vehicle-to-cloud multipath transmission[C]//IEEE. 2020 International Conference on Computing, Networking and Communications. New York: IEEE, 2020: 428-433.
    [72]
    HAN Jiang-ping, XUE Kai-ping, XING Yi-tao, et al. Leveraging coupled BBR and adaptive packet scheduling to boost MPTCP[J]. IEEE Transactions on Wireless Communications, 2021, 20(11): 7555-7567. doi: 10.1109/TWC.2021.3085661
    [73]
    OH B H, LEE J. Feedback-based path failure detection and buffer blocking protection for MPTCP[J]. IEEE/ACM Transactions on Networking, 2016, 24(6): 3450-3461. doi: 10.1109/TNET.2016.2527759
    [74]
    王同军. 中国智能高铁发展战略研究[J]. 中国铁路, 2019(1): 9-14. https://www.cnki.com.cn/Article/CJFDTOTAL-TLZG201901002.htm

    WANG Tong-jun. Study on the development strategy of China intelligent high speed railway[J]. China Railway, 2019(1): 9-14. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-TLZG201901002.htm
    [75]
    ZHANG Han, LI Wen-zhong, GAO Shao-hua, et al. ReLeS: A neural adaptive multipath scheduler based on deep reinforcement learning[C]//IEEE. 2019 IEEE Conference on Computer Communications. New York: IEEE, 2019: 1648-1656.
    [76]
    LI Wen-zhong, ZHANG Han, GAO Shao-hua, et al. SmartCC: a reinforcement learning approach for multipath TCP congestion control in heterogeneous networks[J]. IEEE Journal on Selected Areas in Communications, 2019, 37(11): 2621-2633. doi: 10.1109/JSAC.2019.2933761
    [77]
    YIN Chen-yang, DONG Ping, DU Xiao-jiang, et al. An adaptive network coding scheme for multipath transmission in cellular-based vehicular networks[J]. Sensors, 2020, 20(20): 5902. doi: 10.3390/s20205902
    [78]
    LU Zhao-jun, QU Gang, LIU Zeng-lin. A survey on recent advances in vehicular network security, trust, and privacy[J]. IEEE Transactions on Intelligent Transportation Systems, 2019, 20(2): 760-776. doi: 10.1109/TITS.2018.2818888
    [79]
    MEHRABI M, YOU D H, LATZKO V, et al. Device-enhanced MEC: multi-access edge computing (MEC) aided by end device computation and caching: a survey[J]. IEEE Access, 2019, 7: 166079-166108. doi: 10.1109/ACCESS.2019.2953172
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (989) PDF downloads(100) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return