Typically a user desires to obtain the value of some aggregation function over distributed data items. The authors present a low-cost, scalable technique to answer continuous aggregation queries using a network of aggregators of dynamic data items. In such a network of data aggregators, each data aggregator serves a set of data items at specific coherencies. Their technique involves decomposing a client query into sub-queries and executing sub-queries on judiciously chosen data aggregators with their individual sub-query incoherency bounds. They provide a technique for getting the optimal set of sub-queries with their incoherency bounds, which satisfies client query's coherency requirement with least number of refresh messages sent from aggregators to the client.