Frequency Estimation over Sliding Windows

Capturing characteristics of large data streams has received considerable attention. The constraints in space and time often restrict the data stream processing to only one pass. Furthermore, processing data streams over sliding windows makes the problem more difficult and challenging. In this paper, we address the problem of estimating epsi-approximate frequency in data streams over sliding windows. We are the first who propose an efficient algorithm which can achieve O(1/epsi) space requirement and only need O(1) running time to process each item in the data stream and to answer a query.