Literature by the same author
plus at Google Scholar

Bibliografische Daten exportieren
 

Streamlearner : Distributed incremental machine learning on event streams: Grand challenge

Title data

Mayer, Christian ; Mayer, Ruben ; Abdo, Majd:
Streamlearner : Distributed incremental machine learning on event streams: Grand challenge.
In: Proceedings of the 11th ACM International Conference on Distributed and Event-Based Systems. - New York : Association for Computing Machinery , 2017 . - pp. 298-303
ISBN 978-1-4503-5065-5
DOI: https://doi.org/10.1145/3093742.3095103

Abstract in another language

Today, massive amounts of streaming data from smart devices need to be analyzed automatically to realize the Internet of Things. The Complex Event Processing (CEP) paradigm promises low-latency pattern detection on event streams. However, CEP systems need to be extended with Machine Learning (ML) capabilities such as online training and inference in order to be able to detect fuzzy patterns (e.g. outliers) and to improve pattern recognition accuracy during runtime using incremental model training. In this paper, we propose a distributed CEP system denoted as StreamLearner for ML-enabled complex event detection. The proposed programming model and data-parallel system architecture enable a wide range of real-world applications and allow for dynamically scaling up and out system resources for low-latency, high-throughput event processing. We show that the DEBS Grand Challenge 2017 case study (i.e., anomaly detection in smart factories) integrates seamlessly into the StreamLearner API. Our experiments verify scalability and high event throughput of StreamLearner.

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: 25 Apr 2023 10:52
Last Modified: 05 Feb 2024 07:44
URI: https://eref.uni-bayreuth.de/id/eprint/76022