Reverse Approximate Nearest Neighbor Queries on Road Network

2020 ◽  
Author(s):  
Xinyu Li ◽  
Arif Hidayat ◽  
David Taniar ◽  
Muhammad Aamir Cheema
Keyword(s):  
Road Network ◽  
Nearest Neighbor ◽  
Approximate Nearest Neighbor ◽  
Nearest Neighbor Queries

scholarly journals Efficient Processing of All Nearest Neighbor Queries in Dynamic Road Networks

Mathematics ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 1137
Author(s):  
Aavash Bhandari ◽  
Aziz Hasanov ◽  
Muhammad Attique ◽  
Hyung-Ju Cho ◽  
Tae-Sun Chung
Keyword(s):  
Road Network ◽  
Nearest Neighbor ◽  
Computational Cost ◽  
Road Networks ◽  
Coherence Property ◽  
Traffic Conditions ◽  
Efficient Processing ◽  
Data Objects ◽  
Nearest Neighbor Queries ◽  
Dynamic Road Networks

The increasing trend of GPS-enabled smartphones has led to the tremendous usage of Location-Based Service applications. In the past few years, a significant amount of studies have been conducted to process All nearest neighbor (ANN) queries. An ANN query on a road network extracts and returns all the closest data objects for all query objects. Most of the existing studies on ANN queries are performed either in Euclidean space or static road networks. Moreover, combining the nearest neighbor query and join operation is an expensive procedure because it requires computing the distance between each pair of query objects and data objects. This study considers the problem of processing the ANN queries on a dynamic road network where the weight, i.e., the traveling distance and time varies due to various traffic conditions. To address this problem, a shared execution-based approach called standard clustered loop (SCL) is proposed that allows efficient processing of ANN queries on a dynamic road network. The key concept behind the shared execution technique is to exploit the coherence property of road networks by clustering objects that share common paths and processing the cluster as a single path. In an empirical study, the SCL method achieves significantly better performance than competitive methods and efficiently reduces the computational cost to process ANN queries in various problem settings.

Reverse Approximate Nearest Neighbor Queries

2018 ◽  
Vol 30 (2) ◽  
pp. 339-352 ◽  
Author(s):  
Arif Hidayat ◽  
Shiyu Yang ◽  
Muhammad Aamir Cheema ◽  
David Taniar
Keyword(s):  
Nearest Neighbor ◽  
Approximate Nearest Neighbor ◽  
Nearest Neighbor Queries
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