An efficient and scalable approach to CNN queries in a road network

Hyung Ju Cho, Chin Wan Chung

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

158 Scopus citations

Abstract

A continuous search in a road network retrieves the objects which satisfy a query condition at any point on a path. For example, return the three nearest restaurants from all locations on my route from point 5 to point e. In this paper, we deal with NN queries as well as continuous NN queries in the context of moving objects databases. The performance of existing approaches based on the network distance such as the shortest path length depends largely on the density of objects of interest. To overcome this problem, we propose UNICONS (a unique continuous search algorithm) for NN queries and CNN queries performed on a network. We incorporate the use of precomputed NN lists into Dijkstra's algorithm for NN queries. A mathematical rationale is employed to produce the final results of CNN queries. Experimental results for real-life datasets of various sizes show that UNI-CONS outperforms its competitors by up to 3.5 times for NN queries and 5 times for CNN queries depending on the density of objects and the number of NNs required.

Original languageEnglish
Title of host publicationVLDB 2005 - Proceedings of 31st International Conference on Very Large Data Bases
Pages865-876
Number of pages12
StatePublished - 2005
EventVLDB 2005 - 31st International Conference on Very Large Data Bases - Trondheim, Norway
Duration: 30 Aug 20052 Sep 2005

Publication series

NameVLDB 2005 - Proceedings of 31st International Conference on Very Large Data Bases
Volume2

Conference

ConferenceVLDB 2005 - 31st International Conference on Very Large Data Bases
Country/TerritoryNorway
CityTrondheim
Period30/08/052/09/05

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