Alternative Solutions for Continuous K Nearest Neighbor Queries in Spatial Network Databases

Kolahdouzan, Mohammad R.; Shahabi, Cyrus

doi:10.1007/s10707-005-4575-8

Cited by 87 publications

(92 citation statements)

References 15 publications

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“…One common example of such techniques is the network Voronoi diagrams. Kolahdouzan and Shahabi proposed first network Voronoi based kNN search technique, termed VN3 [7,8]. They retrieve the kNN of a query point q based on precomputed first-order network Voronoi diagram.…”

Section: Related Workmentioning

confidence: 99%

Indexing Network Voronoi Diagrams

Demiryurek

Shahabi

2012

Database Systems for Advanced Applications

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Abstract. The Network Voronoi diagram and its variants have been extensively used in the context of numerous applications in road networks, particularly to efficiently evaluate various spatial proximity queries such as k nearest neighbor (kNN), reverse kNN, and closest pair. Although the existing approaches successfully utilize the network Voronoi diagram as a way to partition the space for their specific problems, there is little emphasis on how to efficiently find and access the network Voronoi cell containing a particular point or edge of the network. In this paper, we study the index structures on network Voronoi diagrams that enable exact and fast response to contain query in road networks. We show that existing index structures, treating a network Voronoi cell as a simple polygon, may yield inaccurate results due to the network topology, and fail to scale to large networks with numerous Voronoi generators. With our method, termed Voronoi-Quad-tree (or VQ-tree for short), we use Quad-tree to index network Voronoi diagrams to address both of these shortcomings. We demonstrate the efficiency of VQ-tree via experimental evaluations with real-world datasets consisting of a variety of large road networks with numerous data objects.

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Section: Related Workmentioning

confidence: 99%

Indexing Network Voronoi Diagrams

Demiryurek

Shahabi

2012

Database Systems for Advanced Applications

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“…The approach proposed in [14] (shown in Figure 3) first determines all possibly qualified objects by drawing a region according to the given range 2) Network-based Approaches: To the best of our knowledge, the approach proposed in [14] is the only one for supporting continuous range queries based on network distances. This approach is motivated by the idea of continuous K-nearest neighbor queries proposed in [15] and [16]. As shown in Figure 4, this approach first selects a segment that contains no intersection node (e.g.…”

Section: B Continuous Range Queriesmentioning

confidence: 99%

Supporting Continuous Range Queries in Indoor Space

Yuan

Schneider

2010

2010 Eleventh International Conference on Mobile Data Management

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Abstract-Range query processing is an important technology in spatial databases. Current studies mainly focus on range queries in outdoor space based on the Euclidean or network distances, but rarely any approach is proposed for indoor space. In this paper, we present two network-based approaches to supporting stationary range queries and continuous range queries for indoor space. There are several challenges involved in designing these approaches. First, having no explicit network construction in indoor space makes it difficult to precisely determine the distances between objects. Second, users can walk to anywhere in the building, which makes it hard to predict users' movements for continuous range queries. Our proposed approaches can overcome these challenges and efficiently support range queries in indoor space.

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“…In the literature, for efficient query processing in road networks, extensive studies have been carried out on indexing [17,35,[21][22][23] and data allocation schemes [25,33,13]. Efficient storage schemes should also be adopted to increase the query performance along with efficient data allocation schemes and index structures.…”

Section: Motivationmentioning

confidence: 99%

A link-based storage scheme for efficient aggregate query processing on clustered road networks

Demir

Aykanat

Cambazoğlu

2010

Information Systems

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a b s t r a c tThe need to have efficient storage schemes for spatial networks is apparent when the volume of query processing in some road networks (e.g., the navigation systems) is considered. Specifically, under the assumption that the road network is stored in a central server, the adjacent data elements in the network must be clustered on the disk in such a way that the number of disk page accesses is kept minimal during the processing of network queries. In this work, we introduce the link-based storage scheme for clustered road networks and compare it with the previously proposed junctionbased storage scheme. In order to investigate the performance of aggregate network queries in clustered road networks, we extend our recently proposed clustering hypergraph model from junction-based storage to link-based storage. We propose techniques for additional storage savings in bidirectional networks that make the linkbased storage scheme even more preferable in terms of the storage efficiency. We evaluate the performance of our link-based storage scheme against the junction-based storage scheme both theoretically and empirically. The results of the experiments conducted on a wide range of road network datasets show that the link-based storage scheme is preferable in terms of both storage and query processing efficiency.

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Alternative Solutions for Continuous K Nearest Neighbor Queries in Spatial Network Databases

Cited by 87 publications

References 15 publications

Indexing Network Voronoi Diagrams

Indexing Network Voronoi Diagrams

Supporting Continuous Range Queries in Indoor Space

A link-based storage scheme for efficient aggregate query processing on clustered road networks

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