The Efficient Processing of Moving k-Farthest Neighbor Queries in Road Networks

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초록

Given a set of facilities F and a query point q, a k-farthest neighbor (kFN) query returns the k farthest facilities f(1) , f(1) ,... , f(k) from q. This study considers the moving k-farthest neighbor (MkFN) query that constantly retrieves the k facilities farthest from a moving query point q in a road network. The main challenge in processing MkFN queries in road networks is avoiding the repeated retrieval of candidate facilities as the query point arbitrarily moves along the road network. To this end, this study proposes a moving farthest search algorithm (MOFA) to compute valid segments for the query segment in which the query point is located. Each valid segment has the same k facilities farthest from the query locations in the valid segment. Therefore, MOFA retrieves candidate facilities only once for the query segment and computes valid segments using these candidate facilities, thereby avoiding the repeated retrieval of candidate facilities when the query point moves. An empirical study using real-world road networks demonstrates the superiority and scalability of MOFA compared to a conventional solution.

키워드

moving k-farthest neighbor query; spatial databases; batch processing algorithm; road network; REVERSE FURTHEST NEIGHBORS; NEAREST-NEIGHBOR
제목
The Efficient Processing of Moving k-Farthest Neighbor Queries in Road Networks
저자
Cho, Hyung-Ju
DOI
10.3390/a15070223
발행일
2022-07
유형
Article
저널명
Algorithms
권
15
호
7