Abstract:

As an essential query, skyline computation over data streams is very important for many online applications, including mobile environment, network monitoring, communication, sensor network and stock market trading, etc. Different from most popular skyline processing methods that deal with the whole data set, this paper focuses on constrained skyline processing over data streams. We employ a grid based index to store the tuples and put forward two algorithms to compute and maintain the skyline set. We also define Influence Area for every query to minimize the cells needed to be processed when new tuples arrive and old tuples expire. Theoretical analysis and experimental evidences show the efficiency of the proposed approach.

Key words: constrained skyline;data stream;grid index