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This paper introduces the concepts of sufficient and necessary sets for distributed processing of probabilistic top-k queries in wireless sensor networks. It develops three algorithms - sufficient set-based, necessary set-based, and boundary-based - to facilitate localized data pruning with bounded intercluster communication rounds in response to dynamic data changes. It also develops an adaptive algorithm that switches between the three algorithms to minimize transmission costs. Experimental results show that the proposed algorithms significantly reduce data transmissions while incurring only small constant communication rounds, and the adaptive algorithm achieves near-optimal performance under various conditions.
