Abstract
Location-aware systems are mobile or spatially distributed computing systems, such as smart phones or sensor nodes in wireless sensor networks, enabled to react flexibly to changing environments. Due to severe restrictions of computational power on these platforms and real-time demands, most current solutions do not support advanced spatial reasoning. Qualitative Spatial Reasoning (QSR) and granularity are two mechanisms that have been suggested in order to make reasoning about spatial environments tractable. We propose an approach for combining these two techniques, so as to obtain a light-weight QSR mechanism, called partial order QSR (for brevity: PQSR), that is fast enough to allow application on small, low-cost computing devices. The key idea of PQSR is to use a core fragment of typical QSR relations, which can be expressed with partial orders and their linearizations, and to additionally delimit reasoning about these relations with a size-based granularity mechanism.
This research was partially supported by the Deutsche Forschungsgemeinschaft (DFG) in the project SenseCast (BE4319/1).
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Schmidtke, H.R., Beigl, M. (2011). Distributed Spatial Reasoning for Wireless Sensor Networks. In: Beigl, M., Christiansen, H., Roth-Berghofer, T.R., Kofod-Petersen, A., Coventry, K.R., Schmidtke, H.R. (eds) Modeling and Using Context. CONTEXT 2011. Lecture Notes in Computer Science(), vol 6967. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24279-3_28
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DOI: https://doi.org/10.1007/978-3-642-24279-3_28
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