Multi-Access Edge Computing-Based Vehicle-Vehicle-RSU Data Offloading Over the Multi-RSU-Overlapped Environment

被引:23
作者
Shih-Yang Lin [1 ]
Chung-Ming Huang [2 ]
Tzu-Yu Wu [2 ]
机构
[1] Shandong Univ Technol, Sch Transportat & Vehicle Engn, Zibo 255049, Shandong, Peoples R China
[2] Natl Cheng Kung Univ, Dept Comp Sci & Informat Engn, Tainan 70101, Taiwan
来源
IEEE OPEN JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS | 2022年 / 3卷
关键词
Servers; Vehicle-to-infrastructure; Cellular networks; Wireless fidelity; Network topology; Decision making; Computer architecture; Multi-access edge computing (MEC); data offloading; road side unit (RSU); RSU handoff; vehicle to vehicle to RSU (VVR); DSRC; TECHNOLOGIES;
D O I
10.1109/OJITS.2022.3142065
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper proposes a predicted k-hop-limited multi-RSU-considered (PKMR) vehicle to vehicle to roadside unit (RSU) (VVR) data offloading method based on the architecture of the Software Defined Network (SDN) controller inside the multi-access edge computing (MEC) server. In the proposed method, a source vehicle that wants to offload data traffic can use a VVR path that connects the source vehicle and the ahead/rear RSU to perform RSU data offloading when the source vehicle approaches the ahead RSU or leaves the rear RSU. Since some RSUs' signal ranges may overlap, multi-RSU deployment and RSU handoff between signal-overlapping RSUs must be managed to utilize VVR-based RSU data offloading as much as possible. Based on a vehicle's periodically reported contexts received by the MEC server, the SDN controller inside the MEC server can execute the proposed PKMR method, which adopts (i) the time-extended prediction mechanism to find the potential VVR paths that exist in a coming time period [tc, tc+T] and (ii) a quality function that takes vehicles' and RSUs' network conditions into consideration to select the most suitable VVR data offloading path. The performance evaluation results indicate that the proposed PKMR method produces better data offloading performance than the traditional self-offloading method.
引用
收藏
页码:7 / 32
页数:26
相关论文
共 23 条
[1]   Interworking of DSRC and Cellular Network Technologies for V2X Communications: A Survey [J].
Abboud, Khadige ;
Omar, Hassan Aboubakr ;
Zhuang, Weihua .
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2016, 65 (12) :9457-9470
[2]   Data Offloading in UAV-Assisted Multi-Access Edge Computing Systems Under Resource Uncertainty [J].
Apostolopoulos, Pavlos Athanasios ;
Fragkos, Georgios ;
Tsiropoulou, Eirini Eleni ;
Papavassiliou, Symeon .
IEEE TRANSACTIONS ON MOBILE COMPUTING, 2023, 22 (01) :175-190
[3]   A Vision of C-V2X: Technologies, Field Testing, and Challenges With Chinese Development [J].
Chen, Shanzhi ;
Hu, Jinling ;
Shi, Yan ;
Zhao, Li ;
Li, Wen .
IEEE INTERNET OF THINGS JOURNAL, 2020, 7 (05) :3872-3881
[4]  
Dijkstra EW., 1959, Numerische Mathematik, V1, P269, DOI [10.1007/BF01386390, DOI 10.1007/BF01386390]
[5]   The k-hop-limited V2V2I VANET data offloading using the Mobile Edge Computing (MEC) mechanism [J].
Huang, Chung-Ming ;
Lin, Shih-Yang ;
Wu, Zhong-You .
VEHICULAR COMMUNICATIONS, 2020, 26
[6]   The Delay-Constrained and Network-Situation-Aware V2V2I VANET Data Offloading Based on the Multi-Access Edge Computing (MEC) Architecture [J].
Huang, Chung-Ming ;
Lai, Chi-Feng .
IEEE OPEN JOURNAL OF VEHICULAR TECHNOLOGY, 2020, 1 :331-347
[7]   V2V Data Offloading for Cellular Network Based on the Software Defined Network (SDN) Inside Mobile Edge Computing (MEC) Architecture [J].
Huang, Chung-Ming ;
Chiang, Meng-Shu ;
Dao, Duy-Tuan ;
Su, Wei-Long ;
Xu, Shouzhi ;
Zhou, Huan .
IEEE ACCESS, 2018, 6 :17741-17755
[8]   Empirical Study of DSRC Performance Based on Safety Pilot Model Deployment Data [J].
Huang, Xianan ;
Zhao, Ding ;
Peng, Huei .
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2017, 18 (10) :2619-2628
[9]   Throughput and Economics of DSRC-Based Internet of Vehicles [J].
Ligo, Alexandre K. ;
Peha, Jon M. ;
Ferreira, Pedro ;
Barros, Joao .
IEEE ACCESS, 2018, 6 :7276-7290
[10]  
Lopez PA, 2018, IEEE INT C INTELL TR, P2575, DOI 10.1109/ITSC.2018.8569938