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The authors use a constrained optimization framework to derive scaling laws for data-centric storage and querying in wireless sensor networks. This paper considers both unstructured sensor networks, which use blind sequential search for querying, and structured sensor networks, which use efficient hash-based querying. The authors find that the scalability of a sensor network's performance depends upon whether or not the increase in energy and storage resources with more nodes is outweighed by the concomitant application-specific increase in event and query loads.
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