A C-V2X Compatible Massive Data Download Scheme Based on Heterogeneous Vehicular Network

被引:8
作者
Yin, Xiuwen [1 ]
Liu, Jianqi [2 ]
Cheng, Xiaochun [3 ]
Xiong, Xiaoming [1 ]
机构
[1] Guangdong Univ Technol, Sch Integrated Circuits, Guangzhou 510006, Peoples R China
[2] Guangdong Univ Technol, Sch Comp Sci & Technol, Guangzhou 510006, Peoples R China
[3] Swansea Univ, Dept Comp Sci, Swansea SA1 8EN, Wales
关键词
Internet of Vehicles; massive download; heterogeneous network; C-V2X; INTERNET; 5G; COMMUNICATION; EFFICIENT; VEHICLES; PROTOCOL; SYSTEM;
D O I
10.1109/TCE.2023.3330940
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Due to the high mobility and limited signal bandwidth, downloading massive data to gathered dense vehicles in traditional IoVs is still rather restricted. Introducing cellular communications into vehicular networks is the intuitive solution for this issue. However, the cellular-communication-based vehicular network has several unavoidable shortcomings such as occupying cellular resources and generating communication charges. To address this issue, we combine heterogeneous network, edge caching and collaborative distribution techniques for downloading massive data in IoVs. Considering the easy deployment and popularity of C-V2X systems in engineering, the proposed scheme is compatible with C-V2X in deployment. Specifically, a comprehensive scheme for intensively downloading massive data to dense vehicles is proposed based on a heterogeneous network, in which the data distribution mode, data scheduling within the cache node, and the matched collaborative distribution algorithms are presented. A new data distribution mode without request-response delay is proposed for distributing data to multiple vehicles with a negligible interval between distributions. The matched algorithms for efficiently realizing the load balance among collaborative vehicles are designed. The simulation results show our scheme can effectively download massive data to dense target vehicles without dependence on cellular communication resources.
引用
收藏
页码:962 / 973
页数:12
相关论文
共 36 条
[1]   Cognitive Communication Device for Vehicular Networking [J].
Ahmed, Zaheer ;
Jamal, Habibullah ;
Khan, Shoab ;
Mehboob, Rizwana ;
Ashraf, Asrar .
IEEE TRANSACTIONS ON CONSUMER ELECTRONICS, 2009, 55 (02) :371-375
[2]  
Baofeng Ji, 2020, IEEE Communications Standards Magazine, V4, P34, DOI [10.1109/mcomstd.001.1900053, 10.1109/MCOMSTD.001.1900053]
[3]   Design and Evaluation of a Collaborative System for Content Diffusion and Retrieval in Vehicular Networks [J].
Barberis, Claudia ;
Malnati, Giovanni .
IEEE TRANSACTIONS ON CONSUMER ELECTRONICS, 2011, 57 (01) :105-112
[4]   Impact of the Generation Interval on the Performance of Sidelink C-V2X Autonomous Mode [J].
Bartoletti, Stefania ;
Masini, Barbara Mavi ;
Martinez, Vincent ;
Sarris, Ioannis ;
Bazzi, Alessandro .
IEEE ACCESS, 2021, 9 :35121-35135
[5]   A Survey of Energy-Efficient Techniques for 5G Networks and Challenges Ahead [J].
Buzzi, Stefano ;
I, Chih-Lin ;
Klein, Thierry E. ;
Poor, H. Vincent ;
Yang, Chenyang ;
Zappone, Alessio .
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, 2016, 34 (04) :697-709
[6]   An Edge Traffic Flow Detection Scheme Based on Deep Learning in an Intelligent Transportation System [J].
Chen, Chen ;
Liu, Bin ;
Wan, Shaohua ;
Qiao, Peng ;
Pei, Qingqi .
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2021, 22 (03) :1840-1852
[7]   LTE-V: A TD-LTE-Based V2X Solution for Future Vehicular Network [J].
Chen, Shanzhi ;
Hu, Jinling ;
Shi, Yan ;
Zhao, Li .
IEEE INTERNET OF THINGS JOURNAL, 2016, 3 (06) :997-1005
[8]   Efficient Maintenance of AODV Routes in the Vehicular Communication Environment with Sparsely Placed Road Side Units [J].
Cho, Chanhyuk ;
Ahn, Sanghyun .
MOBILE INFORMATION SYSTEMS, 2018, 2018
[9]   Edge Computing in VANETs-An Efficient and Privacy-Preserving Cooperative Downloading Scheme [J].
Cui, Jie ;
Wei, Lu ;
Zhong, Hong ;
Zhang, Jing ;
Xu, Yan ;
Liu, Lu .
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, 2020, 38 (06) :1191-1204
[10]   A Comprehensive Survey on Cooperative Intersection Management for Heterogeneous Connected Vehicles [J].
Gholamhosseinian, Ashkan ;
Seitz, Jochen .
IEEE ACCESS, 2022, 10 :7937-7972