Abstract
Sensor networks have emerged as a fundamentally new tool for monitoring spatially distributed phenomena. This paper investigates a strategy by which sensor nodes detect and estimate non-localized phenomena such as “boundaries” and “edges” (e.g., temperature gradients, variations in illumination or contamination levels). A general class of boundaries, with mild regularity assumptions, is considered, and theoretical bounds on the achievable performance of sensor network based boundary estimation are established. A hierarchical boundary estimation algorithm is proposed that achieves a near-optimal balance between mean-squared error and energy consumption.
Supported by the National Science Foundation, grant nos. MIP-9701692 and ANI-0099148, the Office of Naval Research, grant no. N00014-00-1-0390, and the Army Research Office, grant no. DAAD19-99-1-0290.
Supported by the Texas Instruments Visiting Professorship.
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Nowak, R., Mitra, U. (2003). Boundary Estimation in Sensor Networks: Theory and Methods. 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_6
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DOI: https://doi.org/10.1007/3-540-36978-3_6
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