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Source code of the numerical experiments presented in "Energy-Efficient Edge-Facilitated Wireless Collaborative Computing using Map-Reduce" by Antoine Paris, Hamed Mirghasemi, Ivan Stupia and Luc Vandendorpe (presented at SPAWC19).

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Source code of the numerical experiments presented in "Energy-Efficient Edge-Facilitated Wireless Collaborative Computing using Map-Reduce" by Antoine Paris, Hamed Mirghasemi, Ivan Stupia and Luc Vandendorpe (presented at 2019 IEEE 20th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Cannes, France).

Citing this work

@INPROCEEDINGS{8815499,
  author={A. {Paris} and H. {Mirghasemi} and I. {Stupia} and L. {Vandendorpe}},
  booktitle={2019 IEEE 20th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)},
  title={Energy-Efficient Edge-Facilitated Wireless Collaborative Computing using Map-Reduce},
  year={2019},
  volume={},
  number={},
  pages={1-5},
  doi={10.1109/SPAWC.2019.8815499},
  ISSN={},
  month={July},}

Requirements

The code available in this repository was tested with:

  • Python 3.6.7
  • NumPy 1.15.4
  • SciPy 1.1.0
  • matplotlib 3.0.2
  • termcolor 1.1.0 (this one is not strictly useful, it only enhance the readbility of the debug information in the terminal and shows nice colored progress bar while the simulation is running).

Organization

The entire source code is located in src/.

The file core.py contains the "logic" needed (e.g. Algorithm 1 in the paper). The file utils.py contains a small script displaying the progress of a numerical experiments in the terminal while running. The files figure2.py, figures3ab.py and figure3c.py allow to reproduce the figures given in the paper.

Run

To generate Figure 2, run the command

python3 figure2.py

Not that this takes some time.

To generate Figures 3a and 3b, run the command

python3 -O figures3ab.py

(without the -O flag if you want debug information to appear in your terminal). Note that this takes some time.

To generate Figure 3c, run the command

python3 -O figure3c.py

(without the -O flag if you want debug information to appear in your terminal). Note that this takes some time.

Copyright and license

MIT License

Copyright (c) 2019 Université Catholique de Louvain (UCLouvain)

The software provided allows to reproduce the results presented in the research paper "Energy-Efficient Edge-Facilitated Wireless Collaborative Computing using Map-Reduce" by Antoine Paris, Hamed Mirghasemi, Ivan Stupia and Luc Vandendorpe from ICTEAM/ELEN/CoSy (UCLouvain).

Contact: antoine.paris@uclouvain.be

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Acknowledgment

Antoine Paris is a Research Fellow of the F.R.S.-FNRS. This work was also supported by F.R.S.-FNRS under the EOS program (project 30452698, “MUlti-SErvice WIreless NETwork”).

Contact

For feedback, comments, bug reports, etc, please contact antoine.paris@uclouvain.be.

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Source code of the numerical experiments presented in "Energy-Efficient Edge-Facilitated Wireless Collaborative Computing using Map-Reduce" by Antoine Paris, Hamed Mirghasemi, Ivan Stupia and Luc Vandendorpe (presented at SPAWC19).

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