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22nd Congress of the International Society for Photogrammetry and Remote Sensing, ISPRS 2012

作者： Fu, Z. Liu, S. School of Remote and Sensing Wuhan University Wuhan China State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan University China

spatial index impacts upon the efficiency of spatial query seriously in distributed spatial database. In this paper, we introduce a parallel spatial range query algorithm, based on VoMR-tree index, which incorporates Voronoi diagrams into MR-tree, benefiting from the nearest neighbors. We first augments MR-tree to store the nearest neighbors and constructs the VoMR-tree index by Voronoi diagram. We then propose a novel range query algorithm based on VoMR-tree index. In processing a range query, we discuss the data partition method so that we can improve the efficiency by parallelization in distributed database. Just then a verification strategy is promoted. We show the superiority of the proposed method by extensive experiments using data sets of various sizes. The experimental results reveal that the proposed method improves the performance of range query processing up to three times in comparison with the widely-used R-tree variants.

关键词： distributed spatial database Parallel Computing Range Query spatial Index VoMR-tree

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distributed spatial database management for context aware computing systems

Distributed spatial database management for context aware co...

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16th IST Mobile and Wireless Communications

作者： Pils, Carsten Roussaki, Ioanna Strimpakou, Maria Telecommun Software & Syst Grp Waterford Inst Technol Cork Rd Waterford Ireland Natl Tech Univ Athens Sch Elect & Comp Engn GR-10682 Athens Greece

ISBN: (纸本)9781424416622

Context management systems collect large volumes of spatial and non-spatial information. In particular, when these systems cover large areas like cities, countries or even the entire planet, the design of scalable storage, retrieval and delivery mechanisms is paramount. The Daidalos context management system has been design to meet the requirements of large scale systems. This paper presents the Daidalos approach for a scalable distributed data management approach. The system architecture, the management of mobile database nodes and federation issues are described.

关键词： distributed spatial database context management federation

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A global view oriented approach to directory management in distributed spatial database

A global view oriented approach to directory management in d...

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14th International Conference on Geoinformatics

作者： Huang, Zhou Fang, Yu Chen, Bin Yin, Dafei Peng, Xia Peking Univ Inst Remote Sensing & GIS Beijing 100871 Peoples R China

ISBN: (纸本)9780819465276

Based on discussion on general methods of constructing global directory in DSMDS (distributed spatial database Management System), a new approach based on relation model was brought forward. It specifies three main components of the global directory, including directory organization, directory update and extern interface. Then the authors implemented an actual global directory named SDirectoryService as well, key approaches and techniques in implementation were discussed in detail. Some experiments were designed and performed to check the efficiency, correctness and feasibility of the global directory, which reveal the directory works well on each aspect. By using the directory effective global query processing was achieved in DSMDS.

关键词： distributed spatial database directory management global query

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A new parallel spatial query algorithm for distributed spatial databases

A new parallel spatial query algorithm for distributed spati...

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7th International Conference on Machine Learning and Cybernetics

作者： Wei, Hong-Jun Wei, Zu-Kuan Yin, Qian Univ Elect Sci & Technol China Sch Engn & Comp Sci Chengdu 610054 Peoples R China Beijing Normal Univ Coll Informat Sci & Technol Beijing 100875 Peoples R China

ISBN: (纸本)9781424420957

The balance of data and the utilization of resources are essential to distributed spatial database system. The paper presents an efficient parallel spatial query algorithm which takes seriously the organization of spatial data into account. The algorithm adopts a balanced spatial data partitioning strategy for distributed spatial databases. According to the characteristics of data partitioning, it builds a packing R-tree as its index. The strategy also considers the problem of computing distribution. By replicating index to every site, each site can access different entry in the same index node at the same time. Based on the organization of spatial data, the algorithm can simultaneously execute query operation at different site in both filtration phase and refinery phase. So it obviously improves spatial query performances. In order to solve multiple paths search problem caused by R-tree index, the algorithm brings in globe stack to buffer temporary index nodes. It settles the difficult problem flexibly in distributed spatial databases. For simplicity, the paper discusses the parallel algorithm in 2-dimensional space. Through the experiments conducting on many real datasets, it shows better performance in various spatial query operations.

关键词： distributed spatial database spatial query R-tree globe stack parallel algorithm

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A NEW PARALLEL spatial QUERY ALGORITHM FOR distributed spatial databaseS

A NEW PARALLEL SPATIAL QUERY ALGORITHM FOR DISTRIBUTED SPATI...

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2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)

作者： HONG-JUN WEI ZU-KUAN WEI QIAN YIN School of Computer Science and Engineering University of Electronic Science and Technology of China College of Information Science and Technology Beijing Normal University Beijing 100875 China

关键词： distributed spatial database spatial query R-tree Globe stack Parallel algorithm

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DCAD:a Dual Clustering Algorithm for distributed spatial databases

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Geo-spatial Information Science 2007年第2期10卷 137-144页

作者： ZHOU Jiaogen GUAN Jihong LI Pingxiang State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan University 229 Luoyu Road Wuhan 430079 China.

spatial objects have two types of attributes： geometrical attributes and non-geometrical attributes, which belong to two different attribute domains （geometrical and non-geometrical domains）. Although geometrically scattered in a geometrical domain, spatial objects may be similar to each other in a non-geometrical domain. Most existing clustering algorithms group spatial datasets into different compact regions in a geometrical domain without considering the aspect of a non-geometrical domain. However, many application scenarios require clustering results in which a cluster has not only high proximity in a geometrical domain, but also high similarity in a non-geometrical domain. This means constraints are imposed on the clustering goal from both geometrical and non-geometrical domains simultaneously. Such a clustering problem is called dual clustering. As distributed clustering applications become more and more popular, it is necessary to tackle the dual clustering problem in distributed databases. The DCAD algorithm is proposed to solve this problem. DCAD consists of two levels of clustering： local clustering and global clustering. First, clustering is conducted at each local site with a local clustering algorithm, and the features of local clusters are extracted clustering is obtained based on those features fective and efficient. Second, local features from each site are sent to a central site where global Experiments on both artificial and real spatial datasets show that DCAD is effective and efficient.

关键词： distributed clustering dual clustering distributed spatial database

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