Title data
Tahir, Jawad ; Doblander, Christoph ; Mayer, Ruben ; Frischbier, Sebastian ; Jacobsen, Hans-Arno:
The DEBS 2021 grand challenge: analyzing environmental impact of worldwide lockdowns.
In:
Proceedings of the 15th ACM International Conference on Distributed and Event-Based Systems. -
New York
: Association for Computing Machinery
,
2021
. - pp. 136-141
ISBN 978-1-4503-8555-8
DOI: https://doi.org/10.1145/3465480.3467836
Abstract in another language
The ACM DEBS 2021 Grand Challenge (GC) is the eleventh episode of a series of programming challenge competitions that began in 2011. Every year, participants of the GC are provided with new datasets and practical problems, and the challenge receives novel and high performant solutions from research, academia, and industry. The theme of the DEBS '21 GC is analyzing the environmental effects of COVID-19 restrictions. This year's edition of the GC is the first to explicitly focus on the integration and practicability of the solutions by fostering the use of distributed solutions based on widely-used open-source platforms and by requiring participants to address non-functional properties besides correctness of the solution. This paper describes the dataset used, formalizes the problem statement, and explains the evaluation platform that made dataset distribution and remote evaluation possible with our new virtualized infrastructure.
Further data
Item Type: | Article in a book |
---|---|
Refereed: | Yes |
Institutions of the University: | Faculties Faculties > Faculty of Mathematics, Physics und Computer Science Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science > Chair Data Systems Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science > Chair Data Systems > Chair Data Systems - Univ.-Prof. Dr. Ruben Mayer Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science |
Result of work at the UBT: | No |
DDC Subjects: | 000 Computer Science, information, general works > 004 Computer science |
Date Deposited: | 27 Apr 2023 07:40 |
Last Modified: | 05 Feb 2024 07:33 |
URI: | https://eref.uni-bayreuth.de/id/eprint/76040 |