Abstract
Radio frequency identification (RFID) technology is gaining popularity for many IT related applications. Nevertheless, an immediate adoption of RFID solutions by the existing IT infrastructure is a formidable task because of the volume of data that can be collected in a large-scale deployment of RFIDs. In this paper we present algorithms for temporal and spatial aggregation of RFID data streams, as a means to reduce their volume in an application controllable manner. We propose algorithms of increased complexity that can aggregate the temporal records indicating the presence of an RFID tag using an application-defined storage upper bound. We further present complementary techniques that exploit the spatial correlations among RFID tags. Our methods detect multiple tags that are moved as a group and replace them with a surrogate group ID, in order to further reduce the size of the representation. We provide an experimental study using real RFID traces and demonstrate the effectiveness of our methods.
This work has been supported by the Basic Research Funding Program, Athens University of Economics and Business.
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Bleco, D., Kotidis, Y. (2009). RFID Data Aggregation. In: Trigoni, N., Markham, A., Nawaz, S. (eds) GeoSensor Networks. GSN 2009. Lecture Notes in Computer Science, vol 5659. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02903-5_9
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DOI: https://doi.org/10.1007/978-3-642-02903-5_9
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