Deep PDS Learning for AoI Minimization

Source code for paper Age-Based Scheduling for Mobile Edge Computing: A Deep Reinforcement Learning Approach, written in python and tensorflow.

Usage

python DPDS.py
python DPDS.py --Alg='dpl'
python DPDS.py --Alg='coo'
python DPDS.py --Alg='lpo'

The running data are (i) recorded by the tf.summary module and can be viewed in real time by running tensorboard in the logs directory and (ii) written into matlab format files (.mat) in the data directory after the simulation is finished.

Citation

If you find our code helpful, please consider citing our paper.

@article{he2024age,
  title={Age-Based Scheduling for Mobile Edge Computing: A Deep Reinforcement Learning Approach},
  author={He, Xingqiu and You, Chaoqun and Quek, Tony QS},
  journal={IEEE Transactions on Mobile Computing},
  year={2024},
  publisher={IEEE}
}