Processing moving kNN queries using influential neighbor sets

  • Chuanwen Li
  • , Yu Gu
  • , Jianzhong Qi
  • , Ge Yu
  • , Rui Zhang
  • , Wang Yi

Research output: Contribution to journalConference articlepeer-review

39 Scopus citations

Abstract

The moving k nearest neighbor query, which computes one's k nearest neighbor set and maintains it while at move, is gaining importance due to the prevalent use of smart mobile devices such as smart phones. Safe region is a popular technique in processing the moving k nearest neighbor query. It is a region where the movement of the query object does not cause the current k nearest neighbor set to change. Processing a moving k nearest neighbor query is a continuing process of checking the validity of the safe region and recomputing it if invalidated. The size of the safe region largely decides the frequency of safe region recomputation and hence query processing efficiency. Existing moving k nearest neighbor algorithms lack efficiency due to either computing small safe regions and have to recompute frequently or computing large safe regions (i.e., an order-k Voronoi cell) with a high cost. In this paper, we take a third approach. Instead of safe regions, we use a small set of safe guarding objects. We prove that, as long as the the current k nearest neighbors are closer to the query object than the safe guarding objects, the current k nearest neighbors stay valid and no recomputation is required. This way, we avoid the high cost of safe region recomputation. We also prove that, the region defined by the safe guarding objects is the largest possible safe region. This means that the recomputation frequency of our method is also minimized. We conduct extensive experiments comparing our method with the state-of-the-art method on both real and synthetic data sets. The results confirm the superiority of our method.

Original languageEnglish
Pages (from-to)113-124
Number of pages12
JournalProceedings of the VLDB Endowment
Volume8
Issue number2 2
DOIs
StatePublished - Oct 2014
Externally publishedYes
Event3rd Workshop on Spatio-Temporal Database Management, STDBM 2006, Co-located with the 32nd International Conference on Very Large Data Bases, VLDB 2006 - Seoul, Korea, Republic of
Duration: 11 Sep 200611 Sep 2006

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