Efficient Processing of Relevant Nearest-Neighbor Queries

2016 ◽  
Vol 2 (3) ◽  
pp. 1-28 ◽  
Author(s):  
Christodoulos Efstathiades ◽  
Alexandros Efentakis ◽  
Dieter Pfoser
Keyword(s):  
Nearest Neighbor ◽  
Efficient Processing ◽  
Nearest Neighbor Queries

scholarly journals Efficient Processing of Movingk-Range Nearest Neighbor Queries in Directed and Dynamic Spatial Networks

2016 ◽  
Vol 2016 ◽  
pp. 1-17 ◽  
Author(s):  
Hyung-Ju Cho ◽  
Rize Jin
Keyword(s):  
Location Privacy ◽  
Nearest Neighbor ◽  
Real Life ◽  
Location Based Services ◽  
Spatial Networks ◽  
Weight Changes ◽  
Server Side ◽  
Query Region ◽  
Efficient Processing ◽  
Nearest Neighbor Queries

Ak-range nearest neighbor (kRNN) query in a spatial network finds thekclosest objects to each point in the query region. The essential nature of thekRNN query is significant in location-based services (LBSs), where location-aware queries with query regions such askRNN queries are frequently used because of the issue of location privacy and the imprecision of the associated positioning techniques. Existing studies focus on reducing computation costs at the server side while processingkRNN queries. They also consider snapshot queries that are evaluated once and terminated, as opposed to moving queries that require constant updating of their results. However, little attention has been paid to evaluating movingkRNN queries in directed and dynamic spatial networks where every edge is directed and its weight changes in accordance with the traffic conditions. In this paper, we propose an efficient algorithm called MORAN that evaluates movingk-range nearest neighbor (MkRNN) queries in directed and dynamic spatial networks. The results of a simulation conducted using real-life roadmaps indicate that MORAN is more effective than a competitive method based on a shared execution approach.

Simple and Incremental Nearest-Neighbor Search in Spatio-Temporal Databases

2011 ◽  
pp. 204-224
Author(s):  
Katerina Raptopoulou ◽  
Apostolos N. Papadopoulos ◽  
Yannis Manolopoulos
Keyword(s):  
Traffic Control ◽  
Moving Objects ◽  
Nearest Neighbor ◽  
Nearest Neighbor Search ◽  
Temporal Databases ◽  
Wireless Technologies ◽  
Neighbor Search ◽  
Efficient Processing ◽  
Spatio Temporal ◽  
Nearest Neighbor Queries

The efficient processing of nearest-neighbor queries in databases of moving objects is considered very important for applications such as fleet management, traffic control, digital battlefields and more. Such applications have been rapidly spread due to the fact that mobile computing and wireless technologies nowadays are ubiquitous. This chapter presents important aspects towards simple and incremental nearest-neighbor search for spatio-temporal databases. More specifically, we describe the algorithms that have already been proposed for simple and incremental nearest neighbor queries and present a new algorithm regarding that issue. Finally, we study the problem of keeping a query consistent in the presence of insertions, deletions and updates of moving objects.

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.

Efficient processing of all-k-nearest-neighbor queries in the MapReduce programming framework

2019 ◽  
Vol 121 ◽  
pp. 42-70 ◽  
Author(s):  
Panagiotis Moutafis ◽  
George Mavrommatis ◽  
Michael Vassilakopoulos ◽  
Spyros Sioutas
Keyword(s):  
Nearest Neighbor ◽  
K Nearest Neighbor ◽  
Programming Framework ◽  
Efficient Processing ◽  
Nearest Neighbor Queries

Continuous K Nearest Neighbor Queries of Moving Objects in Road Networks

2010 ◽  
Vol 33 (8) ◽  
pp. 1396-1404 ◽  
Author(s):  
Liang ZHAO ◽  
Luo CHEN ◽  
Ning JING ◽  
Wei LIAO
Keyword(s):  
Moving Objects ◽  
Nearest Neighbor ◽  
Road Networks ◽  
Nearest Neighbor Queries
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