Frequent Items Computation over Uncertain Wireless Sensor Network

There is an increasing interest in uncertain and probabilistics databases arising in application domains such as sensor networks, information retrieval, mobile object data management, information extraction, and data integration. A range of different approaches have been proposed to find the frequent items in uncertain database. But there is little work on processing such query in distributed, in-network inference, such as sensor network. In sensor network, communication is the primary problem because of limited batteries. In this paper, a synopsis with minimum amount tuples is proposed, which sufficient for answering the top-k query. And this synopsis can be dynamic maintained with new tuples been added. A novel communication efficient algorithm is presented in taking advantage of this synopsis. The test results confirm the effectiveness and efficiency of our approaches.