Abstract
High-level query languages are an attractive interface for sensor networks, potentially relieving application programmers from the burdens of distributed, embedded programming. In research to date, however, the proposed applications of such interfaces have been limited to simple data collection and aggregation schemes. In this paper, we present initial results that extend the TinyDB sensornet query engine to support more sophisticated data analyses, focusing on three applications: topographic mapping, wavelet-based compression, and vehicle tracking. We use these examples to motivate the feasibility of implementing sophisticated sensing applications in a query-based system, and present some initial results and research questions raised by this agenda.
This work partially supported by NSF grants IIS-0086057 and SI0122599, by DARPA grant F33615-01-C-1895, and by funds from IBM, Intel, Microsoft, and the UC Micro program.
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Hellerstein, J.M., Hong, W., Madden, S., Stanek, K. (2003). Beyond Average: Toward Sophisticated Sensing with Queries. In: Zhao, F., Guibas, L. (eds) Information Processing in Sensor Networks. IPSN 2003. Lecture Notes in Computer Science, vol 2634. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36978-3_5
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