Conference contribution
(Original article)


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


Publication Details
Author(s): Löffler C, Mutschler C, Philippsen M
Publication year: 2015
Conference Proceedings Title: Proceedings of the 9th ACM International Conference on Distributed Event-Based Systems (DEBS'15)
Pages range: 360-363
ISBN: 978-1-4503-3286-6

Event details
Event: 9th ACM International Conference on Distributed Event-Based Systems (DEBS'15)
Event location: Oslo, Norway
Start date of the event: 29/06/2015
End date of the event: 03/07/2015
Language: English

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.



Focus Area of Individual Faculties


How to cite
APA: Löffler, C., Mutschler, 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).

MLA: Löffler, Christoffer, Christopher Mutschler, 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.

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