Our paper "Grand Challenge: Incremental Stream Query Analytics" written by Pedro Silva, Wang Yue, and Tilmann Rabl has been accepted at the DEBS Grand Challenge 2020 (https://2020.debs.org/call-for-grand-challenge-solutions/).
Applications in the Internet of Things (IoT) create many data processing challenges because they have to deal with massive amounts of data and low latency constraints. The DEBS Grand Challenge 2020 specifies an IoT problem whose objective is to identify special type of events in a stream of electricity smart meters data. In this work, we present the Sequential Incremental DBSCAN-based Event Detection Algorithm (SINBAD), a solution based on an incremental version of the clustering algorithm DBSCAN and scenario specific data processing optimizations. SINBAD manages to calculate solutions up to 7 times faster and up to 26% more accurate than the baseline provided by the DEBS Grand Challenge.
The full paper is available here and the video of the presentation is available here.