A safe zone based approach for monitoring moving skyline queries

Abstract

Given a set of criterions, an object o dominates another object o ′ if o is more preferable than o ′ according to every criterion. A skyline query returns every object that is not dominated by any other object. In this paper, we study the problem of continuously monitoring a moving skyline query where one of the criterions is the distance between the objects and the moving query. We propose a safe zone based approach to address the challenge of efficiently updating the results as the query moves. A safe zone is the area such that the results of a query remain unchanged as long as the query lies inside this area. Hence, the results are required to be updated only when the query leaves its safe zone. Although the main focus of this paper is to present the techniques for Euclidean distance metric, the proposed techniques are applicable to any metric distance (e.g., Manhattan distance, road network distance). We present several non-trivial optimizations and propose an efficient algorithm for safe zone construction. Our experiments demonstrate that the cost of our safe zone based approach is reasonably close to a lower bound cost and is three orders of magnitude lower than the cost of a naïve algorithm.

Efficient Geometric Pruning Strategies for Continuous Skyline Queries

“…al [21] presented an algorithm to update the skyline when the data objects change their attribute values. Cheema et al [22] proposed a safe zone-based approach for monitoring moving skyline queries which allows queries to move in an arbitrary fashion. The query results are required to be updated only when the query leaves its safe zone.…”

“…Input: the position of a query point q Output: the initial skyline IS for q, the event queue Q with initial events 21 CreateEvents(s i , q); 22 Compute possible in events with LL.last; Algorithm 2 has shown the process of CreateEvents in detail. For a given skyline point s i , the algorithm first computes the time t when s i and the next skyline point s j in LL will exchange their positions in the list that s j will dominate s i in distance.…”

Within Skyline Query Processing in Dynamic Road Networks

“…Several processing methods have been proposed to solve the continuous skyline query in Euclidean spaces. Cheema et al [14] study the problem of continuously monitoring a moving skyline query by using a safe zone-based approach. Zheng et al [15] propose continuous skyline computation over an incremental motion model, where the query point moves incrementally in discrete time steps with no restrictions and predictability.…”

“…The related works mentioned above focus exclusively on: (1) processing the skyline queries in Euclidean spaces (e.g., [14,15]), where the distance between objects is computed by simply using the objects' locations rather than based on the connectivity of the road network; (2) answering the traditional skyline queries and their variants in the road networks (e.g., [7,17,18]); or (3) considering the continuous skyline query processing in a static road network (e.g., [8,22]), in which the information of objects and the conditions of the roads remain unchanged. In this paper, our efforts are devoted to overcoming the limitations of the previous works.…”

Continuous Skyline Queries for Moving Objects in Road Networks

“…Mohammad et al studied the skyline query for spatial objects by utilizing surrounding objects [12]. Cheema et al studied a problem of monitoring a moving skyline query and proposed a safe zone based approach [13].…”