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Large-scale online mobility monitoring with exponential histograms

: Kopp, Christine; Mock, Michael; Papapetrou, Odysseas; May, Michael

Preprint urn:nbn:de:0011-n-2564839 (302 KByte PDF)
MD5 Fingerprint: 6de986e8c6f889f77def574b9454efec
Erstellt am: 4.9.2013

Cormode, G.:
First International Workshop on Big Dynamic Distributed Data, BD3 2013. Proceedings : Co-located with International Conference on Very Large Databases (VLDB 2013), Riva del Garda, Italy, August 30, 2013
Riva del Garda, 2013 (CEUR Workshop Proceedings 1018)
International Workshop on Big Dynamic Distributed Data (BD3) <1, 2013, Riva del Garda>
International Conference on Very Large Databases (VLDB) <39, 2013, Riva del Garda>
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IAIS ()
mobility monitoring; exponential histograms; out-of-home advertising; visit events; distributed system; storm

The spread of digital signage and its instantaneous adaptability of content challenges out-of-home advertising to conduct performance evaluations in an online fashion. This implies a tremendous increase in the granularity of evaluations as well as a complete new way of data collection, storage and analysis. In this paper we propose a distributed system for the large-scale online monitoring of poster performance indicators based on the evaluation of mobility data collected by smartphones. In order to enable scalability in the order of millions of users and locations, we use a local data processing paradigm and apply exponential histograms for an efficient storage of visit statistics over sliding windows. In addition to an immediate event centralization we also explore a hierarchical archite cture based on a merging technique for exponential histograms. We provide an evaluation on the basis of a real-world data set containing more than 300 million GPS points corresponding to the movement activity of nearly 3,000 persons. The experiments show the accuracy and efficiency of our system.