- Titel
- Online Bit Flip Detection for In-Memory B-Trees on Unreliable Hardware
- Zitierfähige Url:
- https://nbn-resolving.org/urn:nbn:de:bsz:14-qucosa2-805010
- Konferenz
- SIGMOD/PODS'14: International Conference on Management of Data. Snowbird Utah, 23. Juni 2014
- Quellenangabe
- DaMoN '14: Proceedings of the Tenth International Workshop on Data Management on New Hardware
Herausgeber: Alfons Kemper
Herausgeber: Ippokratis Pandis
Erscheinungsort: New York
Verlag: ACM
Erscheinungsjahr: 2014
Seiten: 1-9
ISBN: 978-1-4503-2971-2
Artikelnummer: 5 - Erstveröffentlichung
- 2014
- Abstract (EN)
- Hardware vendors constantly decrease the feature sizes of integrated circuits to obtain better performance and energy efficiency. Due to cosmic rays, low voltage or heat dissipation, hardware -- both processors and memory -- becomes more and more unreliable as the error rate increases. From a database perspective bit flip errors in main memory will become a major challenge for modern in-memory database systems, which keep all their enterprise data in volatile, unreliable main memory. Although existing hardware error control techniques like ECC-DRAM are able to detect and correct memory errors, their detection and correction capabilities are limited. Moreover, hardware error correction faces major drawbacks in terms of acquisition costs, additional memory utilization, and latency. In this paper, we argue that slightly increasing data redundancy at the right places by incorporating context knowledge already increases error detection significantly. We use the B-Tree -- as a widespread index structure -- as an example and propose various techniques for online error detection and thus increase its overall reliability. In our experiments, we found that our techniques can detect more errors in less time on commodity hardware compared to non-resilient B-Trees running in an ECC-DRAM environment. Our techniques can further be easily adapted for other data structures and are a first step in the direction of resilient database systems which can cope with unreliable hardware.
- Andere Ausgabe
- Link zum Artikel, der zuerst in der ACM Digital Library erschienen ist.
DOI: 10.1145/2619228.2619233 - Freie Schlagwörter (DE)
- Online-Fehlererkennung, widerstandsfähige Datenbanksysteme, Hardware, B-trees
- Freie Schlagwörter (EN)
- Online error detection, resilient database systems, hardware, B-trees
- Klassifikation (DDC)
- 004
- Verlag
- ACM, New York
- Förder- / Projektangaben
- Deutsche Forschungsgemeinschaft (DFG)
Exzellenzcluster
Zentrum für Perspektiven in der Elektronik Dresden
(EXC 1056)
ID: 194636624 - Version / Begutachtungsstatus
- angenommene Version / Postprint / Autorenversion
- URN Qucosa
- urn:nbn:de:bsz:14-qucosa2-805010
- Veröffentlichungsdatum Qucosa
- 25.08.2022
- Dokumenttyp
- Konferenzbeitrag
- Sprache des Dokumentes
- Englisch
- Lizenz / Rechtehinweis
