With DAW execution spanning multiple data centers, the assumption of centralized access to provenance traces is problematic: Policies prevent access to low-level data, and the general transfer of all monitoring data would induce a severe overhead. As such, a decentralized model is preferable, in which the required computation is pushed to the data sources as much as possible. This subproject aims to explore how query discovery can be realized at distributed sources.
In: Bao, Zhifeng; Sellis, Timos (Ed.): Proceedings of the VLDB 2022 PhD Workshop co-located with the 48th
International Conference on Very Large Databases (VLDB 2022), Sydney,
Australia, September 5, 2022, CEUR-WS.org, 2022.
@inproceedings{sattler2022scalable,
title = {Scalable Discovery of Queries over Event Streams},
author = {Rebecca Sattler},
editor = {Zhifeng Bao and Timos Sellis},
url = {http://ceur-ws.org/Vol-3186/paper_8.pdf},
year = {2022},
date = {2022-01-01},
urldate = {2022-01-01},
booktitle = {Proceedings of the VLDB 2022 PhD Workshop co-located with the 48th
International Conference on Very Large Databases (VLDB 2022), Sydney,
Australia, September 5, 2022},
volume = {3186},
publisher = {CEUR-WS.org},
series = {CEUR Workshop Proceedings},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
