Abstract
The skyline query processing problem has been well studied for many years. The literature on skyline algorithms so far mainly considers static query points on static attributes. With the popular usage of mobile devices along with the increasing number of mobile applications and users, continuous skyline query processing on both static and dynamic attributes has become more pressing. Existing efforts on supporting moving query points assume that the query point moves with only one direction and constant speed. In this paper, we propose continuous skyline computation over an incremental motion model. The query point moves incrementally in discrete time steps with no restrictions and predictability. Geometric properties over incremental motion denoted by a kinetic data structure are utilized to prune the portion of data points not included in final skyline query results. Various geometric strategies are asymptotically proposed to prune the querying dataset, and event-driven mechanisms are adopted to process continuous skyline queries. Extensive experiments under different data sets and parameters demonstrate that the proposed method is robust and more efficient than multiple snapshots of I/O optimal branch-and-bound skyline (BBS) skyline queries.
Highlights
The skyline query [1,2] is a useful operation for many important applications, including multi-criteria optimal decision making
By utilizing the geometric properties as a query point moves under incremental motion model, we prune skyline non-result-related data points, which can accelerate the processing of continuous skyline queries
We address continuous skyline queries on moving query points under the incremental motion model
Summary
The skyline query [1,2] is a useful operation for many important applications, including multi-criteria optimal decision making. Since discrete motion patterns are more suitable for moving points, we utilize the incremental motion model for the continuous skyline queries. Under the incremental motion model, we utilize the geometric properties to prune the region in which the data objects will not be in the final skyline query results. When the query point moves, the data structure decides whether the data object(s) enter(s) the skyline results or goes out of the result set. Event-driven mechanisms are adopted to compute the continuous skyline results when the query point is moving. By utilizing the geometric properties as a query point moves under incremental motion model, we prune skyline non-result-related data points, which can accelerate the processing of continuous skyline queries.
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