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A Unified Approach to Spatial Proximity Query Processing in Dynamic Spatial Networks
by
Cho, Hyung-Ju
in
Algorithms
/ Batch processing
/ dynamic spatial network
/ Location based services
/ nearest neighbor query
/ Optimization techniques
/ Queries
/ range query
/ Relational data bases
/ Ride sharing services
/ Servers
/ spatial proximity query
/ unified batch algorithm
2021
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A Unified Approach to Spatial Proximity Query Processing in Dynamic Spatial Networks
by
Cho, Hyung-Ju
in
Algorithms
/ Batch processing
/ dynamic spatial network
/ Location based services
/ nearest neighbor query
/ Optimization techniques
/ Queries
/ range query
/ Relational data bases
/ Ride sharing services
/ Servers
/ spatial proximity query
/ unified batch algorithm
2021
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Do you wish to request the book?
A Unified Approach to Spatial Proximity Query Processing in Dynamic Spatial Networks
by
Cho, Hyung-Ju
in
Algorithms
/ Batch processing
/ dynamic spatial network
/ Location based services
/ nearest neighbor query
/ Optimization techniques
/ Queries
/ range query
/ Relational data bases
/ Ride sharing services
/ Servers
/ spatial proximity query
/ unified batch algorithm
2021
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A Unified Approach to Spatial Proximity Query Processing in Dynamic Spatial Networks
Journal Article
A Unified Approach to Spatial Proximity Query Processing in Dynamic Spatial Networks
2021
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Overview
Nearest neighbor (NN) and range (RN) queries are basic query types in spatial databases. In this study, we refer to collections of NN and RN queries as spatial proximity (SP) queries. At peak times, location-based services (LBS) need to quickly process SP queries that arrive simultaneously. Timely processing can be achieved by increasing the number of LBS servers; however, this also increases service costs. Existing solutions evaluate SP queries sequentially; thus, such solutions involve unnecessary distance calculations. This study proposes a unified batch algorithm (UBA) that can effectively process SP queries in dynamic spatial networks. With the proposed UBA, the distance between two points is indicated by the travel time on the shortest path connecting them. The shortest travel time changes frequently depending on traffic conditions. The goal of the proposed UBA is to avoid unnecessary distance calculations for nearby SP queries. Thus, the UBA clusters nearby SP queries and exploits shared distance calculations for query clusters. Extensive evaluations using real-world roadmaps demonstrated the superiority and scalability of UBA compared with state-of-the-art sequential solutions.
Publisher
MDPI AG,MDPI
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