An improved sampling algorithm for landmark windows over weighted streaming data

Abstract

This paper discusses the random sampling algorithm for landmark windows over weighted streaming data, and presents a new algorithm by improving weighted random sampling (WRS) algorithm with a reservoir. When a new data item v i with weight w i arrives, a random number u i is generated, and a key k i is calculated by w i and u i for the data item. We maintain a candidate sample set by the keys of data items, and the keys of older data items is decreased periodically. The theoretic analysis and experiments show that the algorithm is effective and efficient for continuous data streams processing.