Deep Reinforcement Learning for Delay-Oriented IoT Task Scheduling in Space-Air-Ground Integrated Network

no code implementations • 4 Oct 2020 • Conghao Zhou, Wen Wu, Hongli He, Peng Yang, Feng Lyu, Nan Cheng, Xuemin, Shen

Our objective is to design a task scheduling policy that minimizes offloading and computing delay of all tasks given the UAV energy capacity constraint.

Scheduling

Deep RL-based Trajectory Planning for AoI Minimization in UAV-assisted IoT

no code implementations • 2019 11th International Conference on Wireless Communications and Signal Processing (WCSP) 2019 • Conghao Zhou, Hongli He, Peng Yang, Feng Lyu, WenWu, Nan Cheng, and Xuemin (Sherman) Shen

Due to the flexibility and low deployment cost, unmanned aerial vehicles (UAVs) have been widely used to assist cellular networks in providing extended coverage for Internet of Things (IoT) networks.

Decision Making Reinforcement Learning (RL) +1