Making filters smart in distributed data stream environments

Monitoring aggregate queries in real-time over distributed streaming environments appears to be a great challenge not only because of the huge data volume and high rate, but also because of the limitation of the network transmission bandwidth. Consequently, ensuring qualified approximate results with economical network consumption becomes one of the most important goals in such scenarios. In this paper, we study how to monitor aggregate queries continuously over distributed environments efficiently by disposing numerous filters at remote sites, in order to transmit only a small part of incoming data to the query site and therefore save the network resource significantly. We also show how to adjust the parameters of a filter continuously when the incoming data distribution at the corresponding remote site changes. Analysis and extensive experimental results demonstrate that our approach outperforms the existing work.