During data analysis workflow (DAW) execution, energy-intensive components such as CPUs, GPUs, and main memory often remain idle when a system is waiting for distributed data access or network data transfers. Therefore, optimizing data access and network usage is essential not only for fast DAW execution, but also for achieving higher efficiency, e.g., in terms of energy, and hence for better sustainability – not least as power and cooling costs continue to rise.
The subproject focuses on the data transport between tasks, including scheduling of transmissions, network capacity management and data placement. The carbon-aware processing depends heavily on the efficient network transfer and data placement, as the network cost can – in the worst case – eliminate the optimization gains.
@inproceedings{DBLP:conf/bigdataconf/WitzkeSLS23,
title = {Proactive Resource Management to Optimize Distributed Workflow Executions},
author = {Joel Witzke and Florian Schintke and Ansgar Lößer and Björn Scheuermann},
editor = {Jingrui He and Themis Palpanas and Xiaohua Hu and Alfredo Cuzzocrea and Dejing Dou and Dominik Slezak and Wei Wang and Aleksandra Gruca and Jerry Chun-Wei Lin and Rakesh Agrawal},
url = {https://doi.org/10.1109/BigData59044.2023.10386493},
doi = {10.1109/BIGDATA59044.2023.10386493},
year = {2023},
date = {2023-12-18},
urldate = {2023-12-18},
booktitle = {IEEE International Conference on Big Data, BigData 2023, Sorrento, Italy, December 15-18, 2023},
pages = {6305–6307},
publisher = {IEEE},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
@inproceedings{kondrateva2023,
title = {Parameter Prioritization for Efficient Transmission of Neural Networks in Small Satellite Applications},
author = {Olga Kondrateva and Stefan Dietzel and Ansgar Lößer and Björn Scheuermann},
doi = {10.1109/MedComNet58619.2023.10168858},
year = {2023},
date = {2023-06-15},
urldate = {2023-06-15},
booktitle = {2023 21st Mediterranean Communication and Computer Networking Conference (MedComNet)},
pages = {39-42},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
@inproceedings{10168858,
title = {Parameter Prioritization for Efficient Transmission of Neural Networks in Small Satellite Applications},
author = {Olga Kondrateva and Stefan Dietzel and Ansgar Lößer and Björn Scheuermann},
doi = {10.1109/MedComNet58619.2023.10168858},
year = {2023},
date = {2023-01-01},
urldate = {2023-01-01},
booktitle = {2023 21st Mediterranean Communication and Computer Networking Conference (MedComNet)},
pages = {39-42},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
@inproceedings{bader2022towards,
title = {Towards Advanced Monitoring for Scientific Workflows},
author = {Jonathan Bader and Joel Witzke and Soeren Becker and Ansgar Lößer and Fabian Lehmann and Leon Doehler and Anh Duc Vu and Odej Kao},
url = {https://arxiv.org/pdf/2211.12744.pdf},
doi = {10.1109/BigData55660.2022.10020864},
year = {2022},
date = {2022-12-21},
urldate = {2022-12-21},
booktitle = {2022 IEEE International Conference on Big Data (IEEE BigData 2022)},
publisher = {IEEE},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
@inproceedings{10020255,
title = {BottleMod: Modeling Data Flows and Tasks for Fast Bottleneck Analysis (Poster)},
author = {Ansgar Lößer and Joel Witzke and Florian Schintke and Björn Scheuermann},
doi = {10.1109/BigData55660.2022.10020255},
year = {2022},
date = {2022-12-21},
urldate = {2022-12-21},
booktitle = {2022 IEEE International Conference on Big Data (Big Data)},
pages = {6769-6771},
note = {extended preprint: https://doi.org/10.48550/arXiv.2209.05358},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
@article{DBLP:journals/corr/abs-2209-05358,
title = {BottleMod: Modeling Data Flows and Tasks for Fast Bottleneck Analysis},
author = {Ansgar Lößer and Joel Witzke and Florian Schintke and Björn Scheuermann},
url = {https://doi.org/10.48550/arXiv.2209.05358},
doi = {10.48550/ARXIV.2209.05358},
year = {2022},
date = {2022-09-12},
urldate = {2022-01-01},
journal = {CoRR},
volume = {abs/2209.05358},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
