activity
20142023
most citedDeep Reinforcement Learning for Collaborative Edge Computing in Vehicular Networks

254 citations · 917 across the 42 of their papers we have counts for

collaborators
Showing 2019 · cs.NIShow all

7 papers · 2 filters

cs.NI2019

Hierarchical Soft Slicing to Meet Multi-Dimensional QoS Demand in Cache-Enabled Vehicular Networks

Shan Zhang, Hongbin Luo, Junling Li +2

Vehicular networks are expected to support diverse content applications with multi-dimensional quality of service (QoS) requirements, which cannot be realized by the conventional o…

cs.NI2019★ 105 cited

Multi-Drone 3D Trajectory Planning and Scheduling in Drone Assisted Radio Access Networks

Weisen Shi, Junlng Li, Nan Cheng +4

Drone base station (DBS) is a promising technique to extend wireless connections for uncovered users of terrestrial radio access networks (RAN). To improve user fairness and networ…

cs.NI2019★ 10 cited

3D Multi-Drone-Cell Trajectory Design for Efficient IoT Data Collection

Weisen Shi, Junling Li, Nan Cheng +5

Drone cell (DC) is an emerging technique to offer flexible and cost-effective wireless connections to collect Internet-of-things (IoT) data in uncovered areas of terrestrial networ…

cs.NI2019

Delay-Aware Flow Migration for Embedded Services in 5G Core Networks

Kaige Qu, Weihua Zhuang, Qiang Ye +4

Service-oriented virtual network deployment is based on statistical resource demands of different services, while data traffic from each service fluctuates over time. In this paper…

cs.NI2019

An SDN-Based Transmission Protocol with In-Path Packet Caching and Retransmission

Jiayin Chen, Si Yan, Qiang Ye +7

In this paper, a comprehensive software-defined networking (SDN) based transmission protocol (SDTP) is presented for fifth generation (5G) communication networks, where an SDN cont…

cs.NI2019

Bi-Directional Mission Offloading for Agile Space-Air-Ground Integrated Networks

Sheng Zhou, Guangchao Wang, Shan Zhang +3

Space-air-ground integrated networks (SAGIN) provide great strengths in extending the capability of ground wireless networks. On the other hand, with rich spectrum and computing re…

cs.NI2019★ 5 cited

Spectrum Resource Management for Multi-Access Edge Computing in Autonomous Vehicular Networks

Haixia Peng, Qiang Ye, Xuemin Shen

In this paper, a dynamic spectrum management framework is proposed to improve spectrum resource utilization in a multi-access edge computing (MEC) in autonomous vehicular network (…