range aggregate processing spatial databases

Efficient processing of reverse nearest neighborhood queries in spatial

This paper presents a novel query for spatial databases, called reverse nearest neighborhood (RNH) query, to discover the neighborhoods that find a query facility as their nearest facility among other facilities in the dataset. Unlike a reverse nearest neighbor (RNN) query, an RNH query emphasizes on group of users instead of an …

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Range Aggregate Processing in Spatial Databases

This paper studies spatial indexes that solve such queries efficiently and proposes the aggregate Point-tree (aP-tree), which achieves logarithmic cost to the data set …

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Range Aggregate Processing in Spatial Databases

A range aggregate query returns summarized information about the points falling in a hyper-rectangle (e.g., the total number of these points instead of their concrete ids). This paper studies spatial indexes that solve such queries efficiently and proposes the aggregate Point-tree (aP-tree), which achieves logarithmic cost to the data set …

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Efficient Maximum Range Search on Remote Spatial Databases …

Supporting aggregate range queries on remote spatial databases suffers from 1) huge and/or large numbers of databases, and 2) limited type of access interfaces.

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MRFM: An Efficient Approach to Spatial Join Aggregate

Spatial join aggregate(SJA) is a commonly used but time-consuming operation in spatial database. Since it involves both the spatial join and the aggregate operation, performing SJA is a challenging task especially facing the deluge of spatial data. A popular model nowadays for massive data processing is the shared-nothing cluster …

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Range aggregate processing in spatial databases

Figure 2.2: Representation of temporal data - "Range aggregate processing in spatial databases" ... "Range aggregate processing in spatial databases" Skip to search form Skip to main content Skip to account menu. Semantic Scholar's Logo. Search 217,673,117 papers from all fields of science.

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A scalable algorithm for maximizing range sum in spatial databases

A scalable algorithm for maximizing range sum in spatial databases. A scalable algorithm for maximizing range sum in spatial databases. Chin-Wan Chung. 2012, Proceedings of the VLDB Endowment. See Full PDF Download PDF.

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Approximately processing aggregate range queries on remote spatial

Processing aggregate range queries on remote spatial databases suffers from accessing huge and/or large number of databases that operate autonomously and simple and/or restrictive web API interfaces.

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Range Aggregate Processing in Spatial Databases

A range aggregate query returns summarized information about the points falling in a hyper-rectangle (e.g., the total number of these points instead of their concrete ids). This …

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Authenticated indexing for outsourced spatial databases

In spatial database outsourcing, a data owner delegates its data management tasks to a location-based service (LBS), which indexes the data with an authenticated data structure (ADS). The LBS receives queries (ranges, nearest neighbors) originating from several clients/subscribers. ... Range aggregate processing in spatial databases Author(s ...

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Algorithms for Fundamental Spatial Aggregate …

spatial aggregates is devoted to mechanisms to support range queries, or box queries. Aggregate range queries perform some aggregate operation over spatial or …

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A Scalable Algorithm for Maximizing Range Sum in …

spatial preference queries. In this paper, we solve the maximizing range sum (MaxRS) problem in spatial databases. Given a set O of weighted points (a.k.a. objects) and a rectangle r of a given size, the goal of the MaxRS problem is to ﬁnd a location of r which maximizes the sum of the weights of all the objects covered by r.

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ESTA: An Efficient Spatial-Temporal Range Aggregation …

compared with the baseline spatial-temporal range aggre-gation query processing algorithm in terms of the query delay and energy consumption. The remainder of the paper is organized as follows. Section 2summarizes the state-of-the-art in spatial-temporal range ag-gregation query processing and routing protocols for UAV net …

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Approximately processing aggregate range queries on remote spatial

Processing aggregate range queries on remote spatial databases suffers from accessing huge and/or large number of databases that operate autonomously and simple and/or restrictive web API interfaces. To overcome these difficulties, this paper applies a revised version of regular polygon-based search algorithm (RPSA) to …

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Distance browsing in spatial databases

The incremental nearest neighbor algorithm significantly outperforms the existing k-nearest neighbor algorithm for distance browsing queries in a spatial database that uses the R-tree as a spatial index and it is proved informally that at any step in its execution the incremental nearest neighbors algorithm is optimal with respect to the …

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An Introduction to Spatial Databases and Geospatial Data

Understanding Geospatial Data. To understand the world of geospatial data, we need to grasp a few basic concepts: Coordinates are geographic "addresses" using latitude and longitude.; Projections transform the Earth's 3D surface onto 2D maps, preserving various spatial attributes.; Datums are reference systems that define the …

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Range Aggregate Processing in Spatial Databases

Range Aggregate Processing in Spatial Databases. Yufei Tao and Dimitris Papadias. arized information about the points falling in a hyper-rectangle (e.g., the total …

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Range aggregate processing in spatial databases

A range aggregate query returns summarized information about the points falling in a hyper-rectangle (e.g., the total number of these points instead of their concrete ids). This paper studies spatial indexes that solve such queries efficiently and proposes the aggregate Point-tree (aP-tree), which achieves logarithmic cost to the data set …

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Clustering spatial networks for aggregate query processing: …

We evaluate our clustering hypergraph model and recursive bipartitioning schemes on a wide range of road network datasets. The results of the conducted experiments show that the proposed model is quite effective in reducing the number of disk accesses incurred by the network operations. ... Range aggregate processing in …

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A Scalable Algorithm for Maximizing Range Sum in …

spatial preference queries . In this paper, we solve the maximizing range sum (MaxRS ) problem in spatial databases. Given a set O of weighted points (a.k.a. objects) and a rectangle r of a given size, the goal of the MaxRS problem is to nd a location of r which maximizes the sum of the weights of all the objects covered by r.

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Analyzing the performance of NoSQL vs. SQL databases for Spatial …

Initial results suggest that MongoDB performs better by an average factor of 10x-25x which increases exponentially as the data size increases in both indexed and non-indexed operations, and NoSQL databases may be better suited for simultaneous multiple-user query systems including Web-GIS and mobile-GIS. : Relational databases have been …

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Progressive approximate aggregate queries with a multi …

This work presents an algorithm for answering aggregate queries in multi-dimensional databases, using selective traversal of a Multi-Resolution Aggregate (MRA) tree structure storing point data, and shows that even for exact answering the proposed data structure and algorithm are very fast. Answering aggregate queries like SUM, …

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Approximately processing aggregate range queries on …

To overcome these difficulties, this paper applies a revised version of regular polygon-based search algorithm (RPSA) to approximately search aggregate range …

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Efficient processing of all neighboring object group queries …

We present a new type of location-based queries, namely the Budget Range-based All Neighboring Object Group Query (BR-ANOGQ for short), to offer spatial object information while respecting distance and budget range constraints. This query type finds utility in numerous practical scenarios, such as assisting travelers in selecting …

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(PDF) Spatial Databases: An Overview

The study focuses on the data models, query Language, query processing, indexes and query optimization of a spatial databases that approves spatial databases as a necessary tool for data storage ...

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IEEE TRANSACTIONS ON KNOWLEDGE AND DATA …

Range Aggregate Processing in Spatial Databases Yufei Tao and Dimitris Papadias Abstract—A range aggregate query returns summarized information about the points falling in a hyper-rectangle (e.g., the total number of these points instead of their concrete ids). This paper studies spatial indexes that solve such queries efficiently and

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Indexing range sum queries in spatio-temporal databases

The R-tree is known to be one of the most popular index structures to efficiently process window queries in spatial databases. Intuitively, the aggregate R-tree (aR-tree) [7], [10] improves the R-tree's performance in range sum queries by storing, in each intermediate entry, pre-aggregated sums of the objects in the subtree. Fig. 1 …

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Efficient Maximum Range Search on Remote Spatial Databases …

Supporting aggregate range queries on remote spatial databases suffers from 1) huge and/or large numbers of databases, and 2) limited type of access interfaces. This paper applies the Regular Polygon based Search Algorithm (RPSA) to effectively addressing these problems.

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Authenticated indexing for outsourced spatial databases

The MR-tree is introduced, a space-efficient ADS that supports fast query processing and verification and the MR*-tree, a modified version of the MR- tree, which significantly reduces the VO size through a novel embedding technique. In spatial database outsourcing, a data owner delegates its data management tasks to a location …

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A Scalable Algorithm for Maximizing Range Sum in …

We ﬁrst review the range aggregate processing methods in spatial databases. The range aggregate (RA) query was proposed for the scenario where users are interested in sum-marized information about objects in a given range rather than individual objects. Thus, a RA query returns an ag-gregation value over objects qualiﬁed for a given …

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