sbm/sbm range aggregate processing in spatial databases…
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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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A neural database for differentially private spatial range …
Mobile apps and location-based services generate large amounts of location data. Location density information from such datasets benefits research on traffic optimization, context-aware notifications and public …
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A Scalable Algorithm for Maximizing Range Sum in Spatial Databases
W e 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-
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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 using MapReduce.
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ESTA: An Efficient Spatial-Temporal Range Aggregation …
In this paper, we propose an Eficient Spatial-Temporal range Aggregation query processing (ESTA) algorithm for UAV networks. First, a topology change graph is constructed based on the pre-planned trajectory information. Meanwhile, an eficient shortest path algorithm is proposed to obtain the user query delay.
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[PDF] 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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Approximate MaxRS in Spatial Databases
The present paper studies the (1 - e)-approximate MaxRS problem, which admits the same inputs as MaxRS, but aims instead to return a rectangle whose covered weight is at least (1-e)m*, where m* is the optimal covered weight, and e can be an arbitrarily small constant between 0 and 1. In the maximizing range sum (MaxRS) …
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2.1NoSQL vs SQL
This paper attempts to evaluate the performance of an existing NoSQL database 'MongoDB' with its inbuilt spatial functions with that of a SQL database with spatial extension 'PostGIS' for two problems – spatial and aggregate queries, across a range of datasets, with varying features counts.
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Predicted Range Aggregate Processing in Spatio-temporal Databases
A novel accurate prediction index technique, named PRA-tree, is presented, which takes into account both the velocity and space distribution of moving objects and is supplemented by a hash index on IDs ofMoving objects, thus having a good dynamic performance and concurrency. Predicted range aggregate (PRA) query is an important researching issue …
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Analyzing the performance of NoSQL vs. SQL databases for Spatial and
Relational databases have been around for a long time and spatial databases have exploited this feature for close to two decades. The recent past has seen the development of NoSQL non-relational databases, which are now being adopted for spatial object storage and handling, too. While SQL databases face scalability and agility challenges …
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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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Algorithms for Range-Aggregate Query Problems Involving …
We consider variations of the standard orthogonal range searching motivated by applications in database querying and VLSI layout processing. In a generic instance of such a problem, called a range-aggregate query problem we wish to preprocess a set S of geometric objects such that given a query orthogonal range q, a certain intersection or …
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Range Aggregate Processing in Spatial Databases
Range Aggregate Processing in Spatial Databases. Yufei Tao and Dimitris Papadias. Abstract—A range aggregate query returns summarized information about the points …
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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. ... are Web API interfaces available for processing aggregate range queries, RPSA requests a series of k-NN queries to obtain aggregate range query results. ...
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[PDF] Distance browsing in spatial databases | Semantic …
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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Approximate range query processing in spatial network databases …
Spatial range query is one of the most common queries in spatial databases, where a user invokes a query to find all the surrounding interest objects. Most studies in range search consider Euclidean distances to retrieve the result in low cost, but with poor accuracy (i.e., Euclidean distance less than or equal network distance). Thus, …
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Efficient Approximate Range Aggregation over Large …
Range aggregation queries over spatial data returns sum-marized information about the spatial objects falling within a spatial range specified as either a circle or a rectangle [1], …
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Efficient Approximate Range Aggregation over Large …
In this paper, we define the Federated Range Aggregation (FRA) problem and investigate efficient solutions to range aggregation queries over large-scale spatial data federation. Observing that the underlying applications demand real-time. 2375-026X/22/$31.00 ©2022 IEEE DOI 10.1109/ICDE53745.2022.00156. response of high-frequency queries while ...
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Algorithms for Fundamental Spatial Aggregate …
queries, or box queries. Aggregate range queries perform some aggregate operation over spatial or spatiotemporal data that fall into a user speci ed area (the range or box), pos-sibly over some speci ed time window [17, 10, 13]. Such aggregation mechanisms seem to stem from the support for range queries provided by spatial indexing methods such as
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Range aggregate processing in spatial databases
Figure 2.2: Representation of temporal data - "Range aggregate processing in spatial databases"
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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 fitting destinations …
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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 ...
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Range aggregate processing in spatial databases
Figure 4.6: Bulkloading the aP-tree using pooling pages - "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 217,476,902 papers from all fields of science.
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Range aggregate processing in spatial databases | IEEE …
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 cardinality (independently of the query size) for two-dimensional data.
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A Scalable Algorithm for Maximizing Range Sum in …
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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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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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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Continuous visible nearest neighbor query processing in spatial databases
In this paper, we identify and solve a new type of spatial queries, called continuous visible nearest neighbor (CVNN) search. Given a data set P, an obstacle set O, and a query line segment q in a two-dimensional space, a CVNN query returns a set of $${langle p, Rrangle}$$ tuples such that $${p in P}$$ is the nearest neighbor to …
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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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