“Large-Scale Distributed Streaming – Methods and Applications” workshop successfully held at Fraunhofer-Gesellschaft in Munich

In the framework of the 8th Consortium Meeting, which was held from 15th to 17th of June 2016 in Munich, “Large-Scale Distributed Streaming – Methods and Applications” workshop is organized by the FERARI Project in collaboration with Siemens and the LMU Munich.

Large-Scale Distributed Streaming - Methods and Applications

The goal of this workshop was to bring together researchers and practitioners in the field of large-scale distributed streaming in order to discuss current developments at the interface between research and industrial applications. The aims were to foster an exchange between the research communities as well as to promote recent research results to  applications in industry.

LARGE-SCALE DISTRIBUTED STREAMING – METHODS AND APPLICATIONS

Workshop talks:

9:00 9:30 Michael Mock, Fraunhofer IAIS Welcome, Overview on the FERARI Project
9:30 10:00 Daniel Keren, Haifa University Lightweight Monitoring of Distributed Streams Using Convex Bounding Functions
10:00 10:30 Minos Garofalakis, TUC Efficient Analytics over Big, Dynamic, Distributed Data
11:00 11:20 Moshe Gabel, Technion Using Stream Mining Techniques for Machine Health Monitoring
11:20 11:40 Moshe Gabel, Technion Monitoring Least Squares Models of Distributed Streams
11:40 12:10 Assaf Schuster Technion Lazy Detection of Complex Events over Event Streams
12:10 12:40 Antonios Deligiannakis, TUC Optimizing Massive-Scale Complex Event Processing
14:00 14:30 Michael May, Siemens Industrial Data Analytics @ Siemens
14:30 15:00 Volker Tresp, Siemens Machine Learning for Context Sensitive Event Prediction
15:30 16:00 Filippo M. Tilaro, Manuel G. Berges, CERN Data Analytics for CERN Control System
16:00 16:30 Thomas Seidl, LMU Analyzing even faster data streams
16:30 17:00 Matthias Schubert, LMU Monitoring Relational Patterns in Volatile Data Set

The FERARI project (ferari-project.eu) stands for “Flexible Event Processing for Big Data Architectures” It provides communication efficient in-situ solutions for executing complex tasks on large, distributed data streams, such as efficiently identifying sequences of events over distributed sources with complex relations, or learning and monitoring sophisticated abstract models of the data. The FERARI architecture for large-scale complex event processing (CEP) over massive, distributed data streams is available as open source.

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