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In large wireless sensor networks (WSNs), each hop might incur varying delays due to medium access contention, transmission and computation delays. Fast and efficient query responses are essential to network performance and maintenance. To save energy in battery-powered sensors, it is desirable that data be aggregated or compressed along the way toward the base-station (BS). The common method to aggregate data from network edge to the BS uses a hard-line precomputed timer that requires sensors near the network edge to respond to a query earlier than sensors in the vicinity of the BS , . Such rigid scheduling ignores the WSNs's topology and stability. Aggregation opportunities are wasted if the query response timer is set incorrectly. Estimating and allocating precise per- hop communication timers for each node in a large WSN is difficult because timing depends on the network dynamics. We develop a novel, generic and scalable method, which we call soft-line recursive response (SRR), that bases response-wait on actual response times to previous queries using a history buffer, and therefore, is tolerant of network faults or temporal delays. Our simulations show that SRR can improve aggregation opportunities up to 120% over the hard-line approach, while increasing delay less than 5%. SRR reduces query response traffic and data redundancy in both homogeneous and heterogeneous static and mobile WSNs with a maximum O(N) transmission overhead in large WSNs of N nodes and O(logb) update cost where b is the history buffer size.