Abstract
Data dissemination is a promising application in vehicular ad-hoc networks (VANETs) to overcome the limitation in the connection time of specific vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) links, and provide efficient large data file transfer from road-side units (RSUs) to vehicles therein. Unmanned aerial vehicles (UAVs), recently regarded as an effective supplement in wireless networks, can provide line-of-sight (LoS) links with better channel quality, and their high flexibility and maneuverability are beneficial for on-demand deployment in communication systems. In this paper, by employing UAVs as flying relays with data caching capability in VANETs, we design an enhanced UAV-aided data dissemination protocol. Specifically, we propose a centralized UAV trajectory scheduling algorithm based dynamic programming (CTS-DP) to optimize the flying routes of UAVs. Then, based on the scheduled trajectories of UAVs, we further propose a centralized UAV-aided data dissemination scheduling strategy to achieve both effective and efficient coordination of the RSUs, UAVs, and vehicles for data dissemination. Numerical simulations in vehicular scenarios verify the efficiency of the proposed protocol with dynamic UAV trajectory scheduling in terms of downloading progress, data dissemination delay, and system throughput.
Original language | English (US) |
---|---|
Title of host publication | 2019 IEEE International Conference on Communications, ICC 2019 - Proceedings |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
ISBN (Electronic) | 9781538680889 |
DOIs | |
State | Published - May 2019 |
Externally published | Yes |
Event | 2019 IEEE International Conference on Communications, ICC 2019 - Shanghai, China Duration: May 20 2019 → May 24 2019 |
Publication series
Name | IEEE International Conference on Communications |
---|---|
Volume | 2019-May |
ISSN (Print) | 1550-3607 |
Conference
Conference | 2019 IEEE International Conference on Communications, ICC 2019 |
---|---|
Country/Territory | China |
City | Shanghai |
Period | 5/20/19 → 5/24/19 |
Bibliographical note
Funding Information:ACKNOWLEDGMENT This work was in part supported by the National Natural Science Foundation of China under Grants 61622101 and 61571020, the Ministry National Key Research and Development Project under Grant 2017YFE0121400, and the Major Project from Beijing Municipal Science and Technology Commission under Grant Z181100003218007.
Publisher Copyright:
© 2019 IEEE.