在P2P網路中，整個系統的統計資訊可以藉由聚合查詢（aggregation queries）得到。而其中對於串流資料(data stream)要能夠提供不受時間影響以及精確的答案是尤其重要的。我們提出了一個在階層式P2P（hierarchical P2P）基於給定限定條件(constraint-based)而能夠進行連續性聚合性查詢（continuous aggregation queries）的方法。我們的方法（簡稱CARE）利用一個由使用者決定的精確容忍度(precision tolerance)去達到精確度與通訊成本(communication cost)的平衡。經由實驗的結果可知，我們的方法大幅降低了通訊成本，並且能夠適應性的（adaptively）、漸進的（progressively）得到在容許範圍之內的答案。

Providing time-dependent and accurate answers to queries over continuous data stream
is crucially required for peer-to-peer (P2P) networks, in which the global statistical information
can be obtained through aggregation queries. We proposed a constraint-based
approach on continuous aggregation queries over hierarchical P2P system. Our technique
(termed CARE) acquires a user-specified precision tolerance that manipulates the
balance between accuracy and communication cost by users’ requests. As shown in
the experimental results, it dramatically reduces the communication cost and obtains the
specified tolerable answers adaptively and progressively.

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