Efficient Updates for Continuous Skyline Computations

• Authors: Yu-Ling Hsueh;Roger Zimmermann;Wei-Shinn Ku
• Venue: DEXA '08 Proceedings of the 19th international conference on Database and Expert Systems Applications
• Year: 2008

We address the problem of maintaining continuous skyline queriesefficiently over dynamic objects with ddimensions. Skyline queries are an important new search capability for multi-dimensional databases. In contrast to most of the prior work, we focus on the unresolved issue of frequent data object updates. In this paper we propose the ESCalgorithm, an Efficient update approach for Skyline Computations, which creates a pre-computed second skylineset that facilitates an efficient and incremental skyline update strategy and results in a quicker response time. With the knowledge of the second skylineset, ESCenables (1) to efficiently find the substitute skyline points from the second skylineset only when removing or updating a skyline point (which we call a first skyline point) and (2) to delegate the most time-consuming skyline update computation to another independent procedure, which is executed after the complete updated query result is reported. We leverage the basic idea of the traditional BBSskyline algorithm for our novel design of a two-threaded approach. The first skyline can be replenished quickly from a small set of second skylines - hence enabling a fast query response time - while de-coupling the computationally complex maintenance of the second skyline. Furthermore, we propose the Approximate Exclusive Data Regionalgorithm (AEDR) to reduce the computational complexity of determining a candidate set for second skyline updates. In this paper, we evaluate the ESCalgorithm through rigorous simulations and compare it with existing techniques. We present experimental results to demonstrate the performance and utility of our novel approach.