In recent years, autonomous driving has attracted a vast amount of attention from both industry and academia, which has introduced large amounts of region-related data. In order to release the burden in core networks caused by the communication demands for such data, various in-vehicle storage (IVS) systems have been widely studied to bring contents closer to users. To cope with the mobility issue hindering the realization of IVS systems, in this paper, we propose a relay selection strategy (RSS) consisting of the relay map construction (RMC) algorithm and the relay pair matching (RPM) algorithm with the assistance of the vehicle route information. By considering both the potential transmission amount and the waiting time, the proposed RSS generates an overall optimal relay assignment for the IVS system. The performance gain of the proposed RSS compared with the baseline is evaluated by a realistic simulator in terms of the relay failure ratio, the retrieval throughput, and the RSU consumption ratio. Simulation results show that the proposed RSS achieves higher efficiency and robustness than the baseline.
|Original language||English (US)|
|Title of host publication||2019 IEEE Global Communications Conference, GLOBECOM 2019 - Proceedings|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|State||Published - Dec 2019|
|Event||2019 IEEE Global Communications Conference, GLOBECOM 2019 - Waikoloa, United States|
Duration: Dec 9 2019 → Dec 13 2019
|Name||2019 IEEE Global Communications Conference, GLOBECOM 2019 - Proceedings|
|Conference||2019 IEEE Global Communications Conference, GLOBECOM 2019|
|Period||12/9/19 → 12/13/19|
Bibliographical noteFunding Information:
This work was in part supported by the Ministry National Key Research and Development Project under Grant 2017YFE0121400, the National Science and Technology Major Project under Grant 2018ZX03001031, the Major Project from Beijing Municipal Science and Technology Commission under Grant Z181100003218007, the open research fund of Key Laboratory of Wireless Sensor Network & Communication under Grant 2017003, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, the National Natural Science Foundation of China under Grants 61622101 and 61571020, and the National Science Foundation under Grant CPS-1932413.
© 2019 IEEE.