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Abstract
In this paper we introduce an advanced platform to label mobile event data with significant subscriber locations in real time. The presented platform is divided into two sections – the learning section and the real-time processing section. During the real-time processing step, we enrich live event streams with significant locations calculated in the learning step using stream and call detail record data. We validate our system by comparing a sample of subscribers' calculated locations with actual locations and give state benchmarks for minimum event counts. The validation confirms that the platform works within desired deviation levels from real locations. The accuracy strongly depends on the event count that we can take into account. Finally, we simulate a real-world scenario and measure the real-time labelling performance of our system. The results of this simulation confirm that our event labelling platform performs sufficiently well to process real event streams for millions of subscribers in real time.
Acknowledgements
The authors gratefully acknowledge the contribution of The Software Technology and Applications Competence Centre (STACC) through Large-scale Mobile Positioning Data Mining (Demograft) project and all the partners in Archimedes project ‘The Real-time Location-based Big Data Algorithms’ for their help in providing the data.
Disclosure statement
No potential conflict of interest was reported by the authors.
Notes
1. The attributes may vary when dealing with different operators.
2. Gateway Mobile Positioning Centre.
3.http://tsusiatsoftware.net/jts/javadoc/com/vividsolutions/jts/triangulate/VoronoiDiagramBuilder.html.
4. We projected the 5500 tps to Thunderbolt with four nodes using the formula nr_of_nodes*0,7*5500.
5. Java Message Service.
6.http://akka.io/.