Subproject B5 investigates means to improve adaptability and portability of DAWs for large-scale analysis of satellite data. DAWs for such problems are often long and involved and include tasks with very heterogeneous resource requirements (in terms of memory, runtime, and bandwidth). As the manner in which the concrete requirements of tools depend on the input data is a-priori unknown, these DAWs are very difficult to schedule. Today, this problem typically is solved by hardwiring data- and infrastructure dependent scheduling decisions into the DAW. B5 will research new methods for adaptive scheduling of DAWs that adapt to the concrete remote sensing scenario. B5 is an interdisciplinary subproject, led by Prof. Hostert, expert in large-scale satellite data analysis, and Prof. Leser, an expert in workflow management systems for large-scale scientific data analysis.
Towards Advanced Monitoring for Scientific Workflows Inproceedings
In: 2022 IEEE International Conference on Big Data (IEEE BigData 2022), IEEE, 2022.
In: 41th International Performance Computing and Communications Conference 2022, IEEE, 2022.
In: 34th International Conference on Scientific and Statistical Database Management (SSDBM 2022), pp. 1–12, ACM, 2022.
ßMACH — A Software Management Guidance Inproceedings
In: Reichelt, David Georg; Müller, Richard; Becker, Steffen; Hasselbring, Wilhelm; Hoorn, André; Kounev, Samuel; Koziolek, Anne; Reussner, Ralf (Ed.): Symposium on Software Performance 2021, CEUR-WS, Leipzig, Germany, 2022.
In: Remote Sensing, vol. 14, no. 3, 2022, ISSN: 2072-4292.
In: 2022 IEEE International Conference on Services Computing (SCC), pp. 39-44, 2022.
FORCE on Nextflow: Scalable Analysis of Earth Observation Data on Commodity Clusters Inproceedings
In: CIKM Workshops, 2021.