TY - GEN
T1 - A User Association Policy for UAV-aided Time-varying Vehicular Networks with MEC
AU - Hang, Bingqing
AU - Zhang, Biling
AU - Wang, Li
AU - Wang, Jingjing
AU - Ren, Yong
AU - Han, Zhu
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/5
Y1 - 2020/5
N2 - Multi-access edge computing (MEC) is viewed as a promising technology to improve the real time video service in vehicular networks. However, in the traditional vehicular networks, the road side units (RSUs) are usually only equipped with communication modules, and the unmanned aerial vehicles(UAVs) are seldom used. In this paper, a new UAV-aided time-varying vehicular network is introduced for vehicle users (VUEs) to obtain better experience, where the RSUs and the UAV are equipped with MEC servers for the real time video transcoding. Considering that the video service always lasts for a period of time, we investigate the user association policy from a long-term perspective. Specifically, to characterize the time-varying features of communication links and the heterogeneity of available resources, we theoretically derive the achievable video chunks and link reliability based on the vehicle mobility model and content caching model. Then, the user association problem is formulated as the utility optimization problem, where both the VUE's quality of experience (QoE) and handover cost are taken into consideration. Furthermore, we propose an improved Dijkstra algorithm to solve the original NP-hard problem after it is transformed to a shortest path selection problem. Finally, by numerical results, we verify that the proposed scheme outperforms existing schemes in terms of the VUE's QoE and the handover numbers.
AB - Multi-access edge computing (MEC) is viewed as a promising technology to improve the real time video service in vehicular networks. However, in the traditional vehicular networks, the road side units (RSUs) are usually only equipped with communication modules, and the unmanned aerial vehicles(UAVs) are seldom used. In this paper, a new UAV-aided time-varying vehicular network is introduced for vehicle users (VUEs) to obtain better experience, where the RSUs and the UAV are equipped with MEC servers for the real time video transcoding. Considering that the video service always lasts for a period of time, we investigate the user association policy from a long-term perspective. Specifically, to characterize the time-varying features of communication links and the heterogeneity of available resources, we theoretically derive the achievable video chunks and link reliability based on the vehicle mobility model and content caching model. Then, the user association problem is formulated as the utility optimization problem, where both the VUE's quality of experience (QoE) and handover cost are taken into consideration. Furthermore, we propose an improved Dijkstra algorithm to solve the original NP-hard problem after it is transformed to a shortest path selection problem. Finally, by numerical results, we verify that the proposed scheme outperforms existing schemes in terms of the VUE's QoE and the handover numbers.
KW - MEC
KW - RSU
KW - UAV
KW - caching
KW - vehicular network
UR - https://www.scopus.com/pages/publications/85087283542
U2 - 10.1109/WCNC45663.2020.9120610
DO - 10.1109/WCNC45663.2020.9120610
M3 - 会议稿件
AN - SCOPUS:85087283542
T3 - IEEE Wireless Communications and Networking Conference, WCNC
BT - 2020 IEEE Wireless Communications and Networking Conference, WCNC 2020 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE Wireless Communications and Networking Conference, WCNC 2020
Y2 - 25 May 2020 through 28 May 2020
ER -