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Data approximation is a popular means to support energy-efficient query processing in sensor networks. Conventional data approximation methods require users to specify fixed error bounds a prior to address the trade-off between result accuracy and energy efficiency of queries. The authors argue that this can be infeasible and inefficient when, as in many real-world scenarios, users are unable to determine in advance what error bounds can lead to affordable cost in query processing. They Envision ?-Approximate Querying (EAQ) to bridge the gap. EAQ is a uniform data access scheme underlying various queries in sensor networks.
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