no code implementations • 12 Apr 2024 • Cui Zhang, Xiao Xu, Qiong Wu, Pingyi Fan, Qiang Fan, Huiling Zhu, Jiangzhou Wang
In this scheme, vehicle s mobility, channel conditions with temporal variations, computational resources with temporal variations, different data amount, transmission channel status of vehicles as well as Byzantine attacks were taken into account. Simulation results show that the proposed scheme effectively improves the safety and accuracy of the global model.
1 code implementation • 2 Aug 2022 • Qiong Wu, Yu Zhao, Qiang Fan, Pingyi Fan, Jiangzhou Wang, Cui Zhang
In addition, we consider the mobility of vehicles and propose a deep reinforcement learning algorithm to obtain the optimal cooperative caching location for the predicted popular contents in order to optimize the content transmission delay.
no code implementations • 19 Jul 2018 • Qiong Wu, Shuzhen Nie, Pingyi Fan, Zhengquan Li, Cui Zhang
In the second step, we first set the minimum average one-hop delay found in the first step as the initial optimization goal and then adopt the swarming approach again to get the one-hop delay of each backbone vehicle balance to the minimum average one-hop delay.
Networking and Internet Architecture