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ICCTS

The source code for the paper entitled "Data Volume-aware Computation Task Scheduling for Smart Grid Data Analytic Applications", accepted to apear in IEEE ICC 2023. A preprint version at https://arxiv.org/abs/2301.11831. Feel free to reach us if you may have any questions.

Citation:

@misc{https://doi.org/10.48550/arxiv.2301.11831,
  doi = {10.48550/ARXIV.2301.11831},
  url = {https://arxiv.org/abs/2301.11831},
  author = {Guo, Binquan and Li, Hongyan and Yan, Ye and Zhang, Zhou and Wang, Peng},
  title = {Data Volume-aware Computation Task Scheduling for Smart Grid Data Analytic Applications},
  publisher = {arXiv},
  year = {2023}
}

Another similar reformulation techniques can be found in our previous paper, which is now available at https://ieeexplore.ieee.org/document/10001450/

@inproceedings{guo2022optimal,
 title={Optimal Job Scheduling and Bandwidth Augmentation in Hybrid Data Center Networks},
 author={Guo, Binquan and Zhang, Zhou and Yan, Ye and Li, Hongyan},
 booktitle={GLOBECOM 2022-2022 IEEE Global Communications Conference},
 pages={5686--5691},
 year={2022},
 organization={IEEE}
}

Baseline code:

The source code related to our baselines from reference paper entitled "When Network Matters: Data Center Scheduling with Network Tasks" can be found at https://gitlab.com/eesdn-others/scheduling-algorithm.