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The future large-scale deployment of pervasive sensor network infrastructures calls for mechanisms enabling the extraction of general-purpose data at limited energy costs. The approach presented in this paper relies on a simple algorithm to let a sensor network self-organize a virtual partitioning in correspondence of spatial regions characterized by similar sensing patterns, and to let distributed aggregation of sensorial data take place on a per-region basis. The result of this process is that a sensor network can be modeled as a collection of virtual macro sensors, each associated to a well-characterized region of the physical environment. Within each region, each physical sensor has the local availability of aggregated data about its region and is able to act as an access point to such data.
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