Approximative Event Processing on Sensor Data Streams (Best Poster and Demostration Award)

Beitrag bei einer Tagung
(Originalarbeit)


Details zur Publikation

Autor(en): Löffler C, Löffler C, Philippsen M
Jahr der Veröffentlichung: 2015
Tagungsband: Proceedings of the 9th ACM International Conference on Distributed Event-Based Systems (DEBS'15)
Seitenbereich: 360-363
ISBN: 978-1-4503-3286-6
Sprache: Englisch


Abstract





Event-Based Systems (EBS) can efficiently analyze large streams of sensor data in near-realtime. But they struggle with noise or incompleteness that is seen in the unprecedented amount of data generated by the Internet of Things



We present a generic approach that deals with uncertain data in the middleware layer of distributed event-based systems and is hence transparent for developers. Our approach calculates alternative paths to improve the overall result of the data analysis. It dynamically generates, updates, and evaluates Bayesian Networks based on probability measures and rules defined by developers. An evaluation on position data shows that the improved detection rate justifies the computational overhead.






 



FAU-Autoren / FAU-Herausgeber

Löffler, Christoffer
Lehrstuhl für Informatik 14 (Maschinelles Lernen und Datenanalytik)
Mutschler, Christopher Dr.-Ing.
Lehrstuhl für Informatik 2 (Programmiersysteme)
Philippsen, Michael Prof. Dr.
Lehrstuhl für Informatik 2 (Programmiersysteme)


Zitierweisen

APA:
Löffler, C., Löffler, C., & Philippsen, M. (2015). Approximative Event Processing on Sensor Data Streams (Best Poster and Demostration Award). In Proceedings of the 9th ACM International Conference on Distributed Event-Based Systems (DEBS'15) (pp. 360-363). Oslo, Norway, NO.

MLA:
Löffler, Christoffer, Christoffer Löffler, and Michael Philippsen. "Approximative Event Processing on Sensor Data Streams (Best Poster and Demostration Award)." Proceedings of the 9th ACM International Conference on Distributed Event-Based Systems (DEBS'15), Oslo, Norway 2015. 360-363.

BibTeX: 

Zuletzt aktualisiert 2019-01-03 um 21:53