Lyapunov-guided Deep Reinforcement Learning for Stable Online Computation Offloading in Mobile-Edge Computing Networks

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Deep Learning LyDROO
Overview

LyDROO

Lyapunov-guided Deep Reinforcement Learning for Stable Online Computation Offloading in Mobile-Edge Computing Networks

PyTorch code to reproduce LyDROO algorithm [1], which is an online computation offloading algorithm to maximize the network data processing capability subject to the long-term data queue stability and average power constraints. It applies Lyapunov optimization to decouple the multi-stage stochastic MINLP into deterministic per-frame MINLP subproblems and solves each subproblem via DROO algorithm. It includes:

About our works

  1. Suzhi Bi, Liang Huang, and Ying-jun Angela Zhang, ``Lyapunov-guided Deep Reinforcement Learning for Stable Online Computation Offloading in Mobile-Edge Computing Networks'', IEEE Transactions on Wireless Communications, 2021, doi:10.1109/TWC.2021.3085319.

About authors

  • Suzhi BI, bsz AT szu.edu.cn

  • Liang HUANG, lianghuang AT zjut.edu.cn

  • Ying Jun (Angela) Zhang, yjzhang AT ie.cuhk.edu.hk

How the code works

  • For LyDROO algorithm, run the file, LyDROO.py
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Comments
  • KeyError: (slice(None, None, None), None)!

    KeyError: (slice(None, None, None), None)!

    Hi, Thank you for sharing the code, when I ran the code, I got the flowing error message, please help me to solve this problem:

    Traceback (most recent call last): File "/content/LyDROO/LyDROOwithTF2conv.py", line 183, in plot_rate(Q, 100, 'Data Queue of WDs') File "/content/LyDROO/LyDROOwithTF2conv.py", line 39, in plot_rate plt.plot(np.arange(len(rate_array))+1, df.rolling(rolling_intv, min_periods=1).mean()) File "/usr/local/lib/python3.7/dist-packages/matplotlib/pyplot.py", line 2763, in plot is not None else {}), **kwargs) File "/usr/local/lib/python3.7/dist-packages/matplotlib/axes/_axes.py", line 1647, in plot lines = [*self._get_lines(*args, data=data, **kwargs)] File "/usr/local/lib/python3.7/dist-packages/matplotlib/axes/_base.py", line 216, in __call__ yield from self._plot_args(this, kwargs) File "/usr/local/lib/python3.7/dist-packages/matplotlib/axes/_base.py", line 332, in _plot_args y = _check_1d(tup[-1]) File "/usr/local/lib/python3.7/dist-packages/matplotlib/cbook/__init__.py", line 1349, in _check_1d ndim = x[:, None].ndim File "/usr/local/lib/python3.7/dist-packages/pandas/core/frame.py", line 2906, in __getitem__ indexer = self.columns.get_loc(key) File "/usr/local/lib/python3.7/dist-packages/pandas/core/indexes/range.py", line 358, in get_loc raise KeyError(key) KeyError: (slice(None, None, None), None)
    opened by alimogharrebi 7
  • Absence of data

    Absence of data

    First of all, I'd like to thank you for the open source codes. If I may ask, where is the data for the Tensorflow version of the LyDROO, thy PyTorch is self generated , how about the Tensorflow version? Thank you.

    opened by Abednego97 2
Owner
Liang HUANG
Liang HUANG
GitHub
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