The Study and Design of QR*-Tree Spatial Indexing Structure

2012 ◽  
Vol 182-183 ◽  
pp. 2030-2034
Author(s):  
Xiao Yu Song ◽  
Yong Hui Wang ◽  
Shou Jin Wang
Keyword(s):  
Spatial Data ◽  
Spatial Database ◽  
Hybrid Structure ◽  
Storage Space ◽  
Spatial Indexing ◽  
Indexing Structure ◽  
Quad Tree ◽  
Huge Data ◽  
Data Volume

In this study, we will discuss a fast spatial indexing structure called QR*-tree based on R*-tree and quad-tree. Now, R*-tree and R-tree are widely used in spatial database as a spatial indexing structure, But for each algorithm alone, it is not suitable for the huge data volume. The hybrid structure that we proposed is composed of many R*-trees based on space partitioned by quad-tree. Although it demands more storage space than R*-tree or quad-tree, it gains better performance in insertion, deletion, and searching especially, and the more the amount of spatial data is, the better performance the hybrid-tree has.

scholarly journals Improving management of spatial data through spatial database

2020 ◽  
Author(s):  
Nikola Kranjčić ◽  
Bojan Đurin ◽  
Dragana Dogančić ◽  
Lucija Plantak
Keyword(s):  
Spatial Data ◽  
Spatial Database

scholarly journals HiBuffer: Buffer Analysis of 10-Million-Scale Spatial Data in Real Time

2018 ◽  
Vol 7 (12) ◽  
pp. 467 ◽  
Author(s):  
Mengyu Ma ◽  
Ye Wu ◽  
Wenze Luo ◽  
Luo Chen ◽  
Jun Li ◽  
...  
Keyword(s):  
Real Time ◽  
Spatial Data ◽  
High Performance ◽  
Large Scale ◽  
Computation Time ◽  
Buffer Analysis ◽  
Data Volume ◽  
Time Buffer ◽  
Real World Datasets ◽  
Spatial Indexes

Buffer analysis, a fundamental function in a geographic information system (GIS), identifies areas by the surrounding geographic features within a given distance. Real-time buffer analysis for large-scale spatial data remains a challenging problem since the computational scales of conventional data-oriented methods expand rapidly with increasing data volume. In this paper, we introduce HiBuffer, a visualization-oriented model for real-time buffer analysis. An efficient buffer generation method is proposed which introduces spatial indexes and a corresponding query strategy. Buffer results are organized into a tile-pyramid structure to enable stepless zooming. Moreover, a fully optimized hybrid parallel processing architecture is proposed for the real-time buffer analysis of large-scale spatial data. Experiments using real-world datasets show that our approach can reduce computation time by up to several orders of magnitude while preserving superior visualization effects. Additional experiments were conducted to analyze the influence of spatial data density, buffer radius, and request rate on HiBuffer performance, and the results demonstrate the adaptability and stability of HiBuffer. The parallel scalability of HiBuffer was also tested, showing that HiBuffer achieves high performance of parallel acceleration. Experimental results verify that HiBuffer is capable of handling 10-million-scale data.

scholarly journals A Survey on Spatio-temporal Data Analytics Systems

2022 ◽  
Author(s):  
Md Mahbub Alam ◽  
Luis Torgo ◽  
Albert Bifet
Keyword(s):  
Programming Languages ◽  
Spatial Data ◽  
Data Analytics ◽  
Spatial Databases ◽  
Location Based Services ◽  
Temporal Data ◽  
Wide Range ◽  
Data Volume ◽  
Spatio Temporal ◽  
Gis Software

Due to the surge of spatio-temporal data volume, the popularity of location-based services and applications, and the importance of extracted knowledge from spatio-temporal data to solve a wide range of real-world problems, a plethora of research and development work has been done in the area of spatial and spatio-temporal data analytics in the past decade. The main goal of existing works was to develop algorithms and technologies to capture, store, manage, analyze, and visualize spatial or spatio-temporal data. The researchers have contributed either by adding spatio-temporal support with existing systems, by developing a new system from scratch, or by implementing algorithms for processing spatio-temporal data. The existing ecosystem of spatial and spatio-temporal data analytics systems can be categorized into three groups, (1) spatial databases (SQL and NoSQL), (2) big spatial data processing infrastructures, and (3) programming languages and GIS software. Since existing surveys mostly investigated infrastructures for processing big spatial data, this survey has explored the whole ecosystem of spatial and spatio-temporal analytics. This survey also portrays the importance and future of spatial and spatio-temporal data analytics.

scholarly journals Large Dataset Classification Using Parallel Processing Concept

2020 ◽  
Vol 4 (4) ◽  
pp. 191
Author(s):  
Mohammad Aljanabi ◽  
Hind Ra'ad Ebraheem ◽  
Zahraa Faiz Hussain ◽  
Mohd Farhan Md Fudzee ◽  
Shahreen Kasim ◽  
...  
Keyword(s):  
Big Data Analytics ◽  
Large Data ◽  
Business Analytics ◽  
Healthcare Applications ◽  
Current Increase ◽  
High Data ◽  
Huge Data ◽  
Data Volume ◽  
Effective Decision Making ◽  
Experimental Findings

Much attention has been paid to large data technologies in the past few years mainly due to its capability to impact business analytics and data mining practices, as well as the possibility of influencing an ambit of a highly effective decision-making tools. With the current increase in the number of modern applications (including social media and other web-based and healthcare applications) which generates high data in different forms and volume, the processing of such huge data volume is becoming a challenge with the conventional data processing tools. This has resulted in the emergence of big data analytics which also comes with many challenges. This paper introduced the use of principal components analysis (PCA) for data size reduction, followed by SVM parallelization. The proposed scheme in this study was executed on the Spark platform and the experimental findings revealed the capability of the proposed scheme to reduce the classifiers’ classification time without much influence on the classification accuracy of the classifier.

scholarly journals A Hybrid Spatial Indexing Structure of Massive Point Cloud Based on Octree and 3D R*-Tree

2021 ◽  
Vol 11 (20) ◽  
pp. 9581
Author(s):  
Wei Wang ◽  
Yi Zhang ◽  
Genyu Ge ◽  
Qin Jiang ◽  
Yang Wang ◽  
...  
Keyword(s):  
Point Cloud ◽  
Nearest Neighbor ◽  
Nearest Neighbor Search ◽  
Index Structure ◽  
Spatial Indexing ◽  
Cloud Data ◽  
Neighbor Search ◽  
Nearest Neighbor Searching ◽  
Indexing Structure ◽  
Balanced Tree

The spatial index structure is one of the most important research topics for organizing and managing massive 3D Point Cloud. As a point in Point Cloud consists of Cartesian coordinates (x,y,z), the common method to explore geometric information and features is nearest neighbor searching. An efficient spatial indexing structure directly affects the speed of the nearest neighbor search. Octree and kd-tree are the most used for Point Cloud data. However, Octree or KD-tree do not perform best in nearest neighbor searching. A highly balanced tree, 3D R*-tree is considered the most effective method so far. So, a hybrid spatial indexing structure is proposed based on Octree and 3D R*-tree. In this paper, we discussed how thresholds influence the performance of nearest neighbor searching and constructing the tree. Finally, an adaptive way method adopted to set thresholds. Furthermore, we obtained a better performance in tree construction and nearest neighbor searching than Octree and 3D R*-tree.

Methodical Spatial Database Design with Topological Polygon Structures

2012 ◽  
Vol 3 (1) ◽  
pp. 21-30
Author(s):  
Jean Damascène Mazimpaka
Keyword(s):  
Design Process ◽  
Spatial Data ◽  
Spatial Databases ◽  
Early Stage ◽  
Spatial Database ◽  
Database Design ◽  
Integrity Constraints ◽  
Data Types ◽  
Data Infrastructure ◽  
Database Development

Spatial databases form the foundation for a Spatial Data Infrastructure (SDI). For this, a spatial database should be methodically developed to accommodate its role in SDI. It is desirable to have an approach to spatial database development that considers maintenance from the early stage of database design and in a flexible way. Moreover, there is a lack of a mechanism to capture topological relations of spatial objects during the design process. This paper presents an approach that integrates maintenance of topological integrity constraints into the whole spatial database development cycle. The approach is based on the concept of Abstract Data Types. A number of topological classes have been identified and modelling primitives developed for them. Topological integrity constraints are embedded into maintenance functions associated with the topological classes. A semi-automatic transformation process has been developed following the principles of Model Driven Architecture to simplify the design process.

scholarly journals A Grid-Based Approach for Measuring Similarities of Taxi Trajectories

Sensors ◽  
2020 ◽  
Vol 20 (11) ◽  
pp. 3118
Author(s):  
Wei Jiao ◽  
Hongchao Fan ◽  
Terje Midtbø
Keyword(s):  
Spatial Data ◽  
Behavior Pattern ◽  
Spatial Data Mining ◽  
Spatial Data Analysis ◽  
Exact Matching ◽  
The Road ◽  
Data Volume ◽  
Grid Codes ◽  
Position Prediction ◽  
Pass Through

Similarity measurement is one of the key tasks in spatial data analysis. It has a great impact on applications i.e., position prediction, mining and analysis of social behavior pattern. Existing methods mainly focus on the exact matching of polylines which result in the trajectories. However, for the applications like travel/drive behavior analysis, even for objects passing by the same route the trajectories are not the same due to the accuracy of positioning and the fact that objects may move on different lanes of the road. Further, in most cases of spatial data mining, locations and sometimes sequences of locations on trajectories are most important, while how objects move from location to location (the exact geometries of trajectories) is of less interest. For the abovementioned situations, the existing approaches cannot work anymore. In this paper, we propose a grid aware approach to convert trajectories into sequences of codes, so that shape details of trajectories are neglected while emphasizing locations where trajectories pass through. Experiments with Shanghai Float Car Data (FCD) show that the proposed method can calculate trajectories with high similarity if these pass through the same locations. In addition, the proposed methods are very efficient since the data volume is considerably reduced when trajectories are converted into grid-codes.

scholarly journals Semitensor Product Compressive Sensing for Big Data Transmission in Wireless Sensor Networks

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Haipeng Peng ◽  
Ye Tian ◽  
Jürgen Kurths
Keyword(s):  
Big Data ◽  
Compressive Sensing ◽  
Data Transmission ◽  
Matrix Multiplication ◽  
Wireless Sensor ◽  
Storage Space ◽  
Secret Key ◽  
Encrypt Data ◽  
The Matrix ◽  
Data Volume

Big data transmission in wireless sensor network (WSN) consumes energy while the node in WSN is energy-limited, and the data transmitted needs to be encrypted resulting from the ease of being eavesdropped in WSN links. Compressive sensing (CS) can encrypt data and reduce the data volume to solve these two problems. However, the nodes in WSNs are not only energy-limited, but also storage and calculation resource-constrained. The traditional CS uses the measurement matrix as the secret key, which consumes a huge storage space. Moreover, the calculation cost of the traditional CS is large. In this paper, semitensor product compressive sensing (STP-CS) is proposed, which reduces the size of the secret key to save the storage space by breaking through the dimension match restriction of the matrix multiplication and decreases the calculation amount to save the calculation resource. Simulation results show that STP-CS encryption can achieve better performances of saving storage and calculation resources compared with the traditional CS encryption.

User Preference Based Spatial Skyline Query Method

2014 ◽  
Vol 530-531 ◽  
pp. 832-838
Author(s):  
Yong Gui Zou ◽  
Zhi Wang
Keyword(s):  
Spatial Data ◽  
Road Network ◽  
User Preference ◽  
Skyline Query ◽  
Data Set ◽  
Second Stage ◽  
Processing Data ◽  
Data Volume ◽  
Definition Of ◽  
Query Algorithm

With the increasing of data volume and data dimensions in road network query, the response gets slow in searching services, which cannot satisfy users demand for preference-based searching. This paper proposes a user preference-based Skyline query algorithm. At the first stage, this method is based on the fact that the static property of data does not change during the query processes. Therefore, Skyline starts its calculation in the non-spatial data set to have the candidate results and dominance relation. Then it calculates the total costs of routine by defining user preference function. At the second stage, compare the data connections with the total costs of preference to minimize time for processing data and searching. The experiment result shows that the definition of user preference meets the users demand, and Skyline query algorithm benefits to have quick response.

Design and Implementation of the Spatial Database for Reclaimed Water Utilization

2013 ◽  
Vol 448-453 ◽  
pp. 1179-1187 ◽  
Author(s):  
Yu Mei Guo ◽  
Rui Tao Cun ◽  
Xiao Xiao Li ◽  
Hong Liang
Keyword(s):  
Water Use ◽  
Spatial Data ◽  
Spatial Database ◽  
Dianchi Lake ◽  
Lake Basin ◽  
Concept Design ◽  
Recycled Water ◽  
Application Requirements ◽  
Spatial Data Model ◽  
The City

In order to meet the application requirements of visual management and analysis of the information about recycled water use, the spatial database for the City Recycled Water Use is designed and constructed in this paper based on Geodatabase the spatial data model as well as UML and CASE as tools. The View Layer design, Concept design and Logic Design of the database of the recycled water use is explained in details. Then the application of the designed database to implement the Dianchi Lake Basin recycled water use in GIS platform is carried out and parts of the details is described in this paper.

Sign in / Sign up

Export Citation Format

Share Document