Distributed Spatial Reasoning for Wireless Sensor Networks
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.
KeywordsPartial order reasoning contextual reasoning qualitative spatial reasoning context-aware computing distributed reasoning
Unable to display preview. Download preview PDF.
- 1.Beigl, M., Gray, P., Salber, D. (eds.): Workshop on Location Modeling for Ubiquitous Computing (2001), http://www.teco.edu/locationws/
- 2.Berchtold, M., Riedel, T., Decker, C., Beigl, M., Bittel, C.: Quality of location: estimation, system integration and application. In: INSS. IEEE, Los Alamitos (2008)Google Scholar
- 3.Choudhury, T., Quigley, A.J., Strang, T., Suginuma, K. (eds.): LoCA 2009. LNCS, vol. 5561. Springer, Heidelberg (2009)Google Scholar
- 6.Ding, Y., Laue, F., Schmidtke, H.R., Beigl, M.: Sensing spaces: Light-weight monitoring of industrial facilities. In: 5th Workshop on Behaviour Monitoring and Interpretation (2010)Google Scholar
- 12.Hobbs, J.: Granularity. In: Josh, A.K. (ed.) Ninth International Joint Conference on Artificial Intelligence, pp. 432–435. Morgan Kaufmann, Los Angeles (1985)Google Scholar
- 14.Randell, D., Cui, Z., Cohn, A.: A spatial logic based on region and connection. In: Knowledge Representation and Reasoning, pp. 165–176. Morgan Kaufmann, San Francisco (1992)Google Scholar
- 15.Schmidtke, H.R.: The house is north of the river: Relative localization of extended objects. In: Montello, D. (ed.) COSIT 2001. LNCS, vol. 2205, pp. 415–430. Springer, Heidelberg (2001)Google Scholar
- 16.Schmidtke, H.R.: A geometry for places: Representing extension and extended objects. In: Kuhn, W., Worboys, M., Timpf, S. (eds.) COSIT 2003. LNCS, vol. 2825, pp. 235–252. Springer, Heidelberg (2003)Google Scholar
- 18.Schmidtke, H.R., Woo, W.: A size-based qualitative approach to the representation of spatial granularity. In: Veloso, M.M. (ed.) International Joint Conference on Artificial Intelligence, pp. 563–568 (2007)Google Scholar