Abstract
Data dissemination is playing a crucial role in improving the connectivity and performance in hybrid vehicular ad-hoc networks (VANETs) by exploiting both vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication links, which can achieve effective data sharing and distribution between road-side units (RSUs) and vehicles. Recently, unmanned aerial vehicles (UAVs), acting as flying base stations (BSs) or relays with caching capability, have been widely investigated as an effective and enhanced communication support from the sky to provide the ground users improved quality of services (QoS) in a variety of circumstances. In this paper, by fully exploiting the advantages of UAVs introduced in VANETs, we design an advanced UAV-aided cooperative data dissemination scheduling strategy to improve the data dissemination performance in VANETs. Considering the mobility of the involved UAVs, we further propose a three-dimensional (3D) spatial dynamic programming (SDP) algorithm for the trajectory scheduling of UAVs to optimize the network transmission utility. Simulations results verify that, compared with other data dissemination strategies, our proposed UAV-aided cooperative data dissemination strategy can efficiently achieve a better system performance in terms of downloading progress and transmission delay.
Original language | English (US) |
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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 |
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Volume | 2019-May |
ISSN (Print) | 1550-3607 |
Conference
Conference | 2019 IEEE International Conference on Communications, ICC 2019 |
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Country/Territory | China |
City | Shanghai |
Period | 5/20/19 → 5/24/19 |
Bibliographical note
Funding Information:ACKNOWLEDGEMENT 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.