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A Scalable Architecture for Real-Time Stream Processing of Spatiotemporal IoT Stream Data—Performance Analysis on the Example of Map Matching

Geodetic Institute and Chair for Computing in Civil Engineering & Geo Information Systems, RWTH Aachen University, Mies-van-der-Rohe-Str. 1, 52074 Aachen, Germany
Advanced Community Information Systems Group (ACIS), RWTH Aachen University, Lehrstuhl Informatik 5, Ahornstr. 55, 52074 Aachen, Germany
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2018, 7(7), 238;
Received: 12 March 2018 / Revised: 7 June 2018 / Accepted: 19 June 2018 / Published: 21 June 2018
(This article belongs to the Special Issue Geospatial Applications of the Internet of Things (IoT))
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Scalable real-time processing of large amounts of data has become a research topic of particular importance due to the continuously rising amount of data that is generated by devices equipped with sensing components. While existing approaches allow for fault-tolerant and scalable stream processing, we present a pipeline architecture that consists of well-known open source tools to specifically integrate spatiotemporal internet of things (IoT) data streams. In a case study, we utilize the architecture to tackle the online map matching problem, a pre-processing step for trajectory mining algorithms. Given the rising amount of vehicle location data that is generated on a daily basis, existing map matching algorithms have to be implemented in a distributed manner to be executable in a stream processing framework that provides scalability. We demonstrate how to implement state-of-the-art map matching algorithms in our distributed stream processing pipeline and analyze measured latencies. View Full-Text
Keywords: stream processing; IoT; spatiotemporal; data mining; map matching stream processing; IoT; spatiotemporal; data mining; map matching

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Laska, M.; Herle, S.; Klamma, R.; Blankenbach, J. A Scalable Architecture for Real-Time Stream Processing of Spatiotemporal IoT Stream Data—Performance Analysis on the Example of Map Matching. ISPRS Int. J. Geo-Inf. 2018, 7, 238.

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