Partitioning of Spatial Data in Publish-Subscribe Messaging Systems

Outersterp, R.M. van (2016) Partitioning of Spatial Data in Publish-Subscribe Messaging Systems.

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Abstract:In this thesis we investigate how spatial partitioning methods can help to scale up publish-subscribe messaging systems for processing big spatial data. For this we present a case study consisting of Apache Kafka, an open-source publish-subscribe messaging system. In the case study the Kafka system processes road traffic data. In our research we discuss existing spatial partitioning methods. We show how one of these, Voronoi, can improve processing of spatial data in a publish-subscribe system when compared to a system without spatial partitioning. In addition, we propose a new spatial partitioning method based on Geohash to overcome several drawbacks of Voronoi. Our experiments show improvements in the areas of load balancing, transferred messages, and the amount of relevant messages when using spatial partitioning methods. We show that in general Geohash was able to achieve better results than Voronoi during our experiments. Only when the amount of partitions is more than half of what Geohash can define, Voronoi shows slightly better results.
Item Type:Essay (Master)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:54 computer science
Programme:Computer Science MSc (60300)
Link to this item:http://purl.utwente.nl/essays/70881
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