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Identifier

000395069

Title

Stream correlation monitoring for uncertainty - aware data processing systems

Alternative Title

Παρακολούθηση συσχετίσεων μεταξύ ροών δεδομένων σε συστήματα επεξεργασίας δεδομένων με αβεβαιότητα

Author

Σεληνιωτάκη, Αλέκα Κ.

Thesis advisor

Χριστοφίδης, Βασίλειος

Reviewer

Τσακαλίδης, Παναγιώτης
Παπαδοπούλη, Μαρία
Τζαγκαράκης, Γεώργιος

Abstract

In several industrial applications, monitoring large - scale infrastructures in order to provide notifications for abnormal behavior is of high significance. For this p urpose, the deployment of large - scale sensor networks is the current trend. However, this results in handling vast amounts of low - level, and often unreliable, data, while an efficient and real - time data manipulation is a strong demand. In this thesis, we p ropose an uncertainty - aware data management system capable of monitoring interrelations between large and heterogeneous sensor data streams in real - time. To this end, an efficient similarity function is employed instead of the typical correlation coefficie nt to monitor dynamic phenomena for timely alerting notifications, and to guarantee the validity of detected extreme events. Experimental evaluation with a set of real data recorded by distinct sensors in an industrial water desalination plant reveals a su perior performance of our proposed approach in terms of achieving significantly reduced execution times, along with increased accuracy in detecting extreme events and highly correlated pairs of sensor data streams, when compared with state-of-the-art data stream processing techniques.

Language

English, Greek

Subject

Uncertainty quantification

Wireless sensor networks

Ασύρματα δίκτυα αισθητήρων

Ποσοτικοποίηση αβεβαιότητας

Issue date

2015-07-17

Collection

School/Department--School of Sciences and Engineering--Department of Computer Science--Post-graduate theses

Type of Work--Post-graduate theses