时空数据库中的时空拓扑查询

1 引言现代社会大量的科学应用,如航空系统的飞行器导航、森林火灾探测、乃至于人们生活中应用越来越广泛的移动通讯手机等等,这些都导致有必要研究一个能兼顾时空两属性的数据库管理系统。研制一个能有效表示和处理时空对象的DBMS,其中一项重要工作就是对时空对象进行空间分析操作。典型的时空对象的分析操作估计有近百个,大致划分为七类:a)时空对象间拓扑关系的操作,如求一个移动点是否在一个移动区域中:b)时空对象与空间对象间拓扑关系的操作,如求一个移动点是否在一个固定区域中;c)返回值为时空对象的操作,如求移动点的轨迹;d)返回值为空间对象的操作,如求一个移动点在某一个特定时刻的空间位置;e)返回值为单个数值的操作,如求一个移动点的速度;f)返回值为多个数值的操作,如求两个移动点间的距离;g)在时空对象集合上的操作,如在一些移动区域上进行FUSION操作。     

时空数据模型研究

当前,相关定位设备及数据库技术的发展使得模拟和查询位置或形状随时间变化的移动物体成为可能。设计时空查询语言是构建移动对象数据库必不可少的步骤。本文在前人研究成果的基础上,提出了时空数据类型以及为了在移动对象数据库中进行时空查询而引入的相关操作符。     

虚拟现实系统中的实体和“行为”

1 什么是实体和“行为”? 我们常说:虚拟环境中存在着众多的实体,每个实体均具有‘行为”。究竟何为实体,何谓“行为”呢?实体是指存在于虚拟环境中有意义的对象。例如:军事模拟中的“飞机”、“坦克”、“士兵”等。如果一个实体具有一系列的特征,则行为就是所有这些特征时刻变化的状态。例如:一实体可能具有称为“位置”的特征,当它移动时,位置便改变。它的位置随时间而变化的这种方式就是它的行为。     

时空相点移动对象数据索引PM-Tree

随着移动定位技术和无线通讯技术发展,移动对象的应用领域越来越广阔.位置随时间而变化的移动对象产生的时空数据具有规模大、多维性、结构复杂和关系复杂等特点.由于移动对象的运动轨迹大多被限定在特定的交通网络中,因此基于路网的移动对象索引成为时空数据索引研究的一个重要应用分支.目前,针对移动对象历史数据的区域查询优化的研究重点...     

基于状态和变化的统一时空数据模型

提出了一个基于状态和变化的统一时空数据模型SCUDM(state and change based unified spatio-temporial datamodel).时空数据库的状态是关于对象、空间和时间的三元组,时空数据库的变化就是状态的变化.按照对象域、空间域和时间域将时空数据库中的变化分别投影分解,显式地表达在对象、空间和时间上的变化.而事件是在某一时刻前后,时空实体的变化关系,在事件表达中蕴涵了空间实体之间的时间拓扑关系.SCUDM不仅支持状态和变化的表达,而且支持时间拓扑和空间拓扑的表达.     

一种混合的时空数据库索引机制

近年来,时空数据库的应用得到迅速发展,在动态时空环境里,维持持续移动对象的位置信息是一个挑战。本文提出了一种新的索引机制,采用两种不同类型的索引结构,一种索引移动对象历史轨迹,一种能够有效地索引移动对象现在、最近、将来的位置信息,而且随着时间的推移,能够将两种索引结构内容快速过渡。在实现移动对象历史轨迹的完整或局部的有效查询的同时,又保证了移动轨迹的空间紧密性。     

一种预测性连续时空区域查询处理方法

预测性连续时空区域查询在用户指定的时间范围期间持续地返回给定未来查询时间范围期间将出现在查询区域的移动对象。论文提出了一种预测性连续时空区域查询处理方法,设计了支持连续查询处理的两种索引结构。移动对象索引用于记录移动对象不断更新的位置信息,它用于支持查询的首次处理。连续查询索引结构用于记录所有查询结果可能受到移动对象位置变化影响的连续查询,它用于支持连续查询处理。实验表明,论文提出的方法能够有效地提高处理大量连续查询的效率。     

一种基于概率模型的预测性时空区域查询处理

提出了一种基于概率模型的预测性时空区域查询处理方法.该方法采用Filter-Refinement方式来处理查询.首先,从数据库中选择所有可能满足查询的候选移动对象;然后,根据概率模型中定义的方法来计算候选移动对象满足查询的概率;最后,根据查询中指定的最小概率阈值过滤候选移动对象并返回查询结果.该概率模型将移动对象未来可能出现的位置定义为一个随机变量,并给出了计算移动对象在两种不同的运动模式下满足查询的概率值的方法.还提出了一种通过对大量历史轨迹抽样来获得概率密度函数(probability density function,简称PDF)的轨迹分析算法,并设计了概率密度函数索引STP-Index(spatio-temporal PDF-index).该索引能够有效地提高轨迹分析算法和概率计算的效率.实验结果表明,该查询处理方法能够有效地支持预测性时空区域查询的处理,提高查询结果的正确性,特别适合于具有较小的空间区域和长时间范围的预测性时空区域查询.     

时空数据库移动点轨迹建模

时空数据库的移动点轨迹建模技术是近年来是时空数据库研究热点之一.本文在给定一系列时空数据库移动点的信息,找出实际应用中时间更新阈值和空间距离阈值,结合移动点时空模型和数学上线性回归的建模思想,建立一种新的支持过去、现在、未来的移动点轨迹模型,并有效地预测了移动点在某一时间阈值内,移动点的运动趋势及范围.     

移动对象数据库模型、查询语言及实时交通流分析

提出一种移动对象数据库模型——Dynamic Transportation Network Based Moving Objects Database(简称DTNMOD),并给出了DTNMOD中基于移动对象时空轨迹的网络实时动态交通流分析方法.在DTNMOD中,交通网络被表示成动态的时空网络,可以描述交通状态、拓扑结构以及交通参数随时间的变化过程;网络受限的移动对象则用网络移动点表示.DTNMOD 模型包含了完整的数据类型和查询操作的定义,因此可以在任何可扩充数据库(如PostgreSQL 或SECONDO)中实现,从而得到完整的数据库模型和查询语言.为了对相关模型的性能进行比较与分析,基于PostgreSQL 实现了一个原型系统并进行了一系列的实验.实验结果表明,DTNMOD 提供了良好的区域查询及连接查询性能.     

时空数据库中数据建模的研究

研究了时空数据库中的时空建模技术。早期表示时空信息的数据模型通常用基于几何学的空间对象来表示实体，重要的特性都用空间对象的属性来表示。时态信息可以与基于时间戳的独立层次相关联，也可以与独立的空间对象相关联。随着时空建模的进一步发展，出现了面向对象的数据模型和基于事件的数据模型。综合研究了这些典型的时空数据模型，讨论了它们的应用及时空分析建模的作用。此外介绍了针对移动对象的数据类型的建模方法，以及在时空分析数据库管理系统STADBS中，基于Realms的二级平衡二叉树的时空数据模型。     

时空数据库索引机制研究

Spatio-temporal database manages the large amount of spatial objects that change over time.It is necessary to query the spatio-temporal objects of the past and the current and to anticipate the future of spatio-temporal objects.It is important to design an efficient index mechanism for accessing the spatio-temporal data efficiently.The paper analyzes the features of the spatio-temporal objects,studies the methods of spatio-temporal index mechanisms,classifies the index mechanisms,and discusses the key technologies of spatio-temporal indexes.And it also presents the index methods of STADBS that we are studying.     

A database perspective on geospatial data modeling

We study the representation and manipulation of geospatial information in a database management system (DBMS). The geospatial data model that we use as a basis hinges on a complex object model, whose set and tuple constructors make it efficient for defining not only collections of geographic objects but also relationships among these objects. In addition, it allows easy manipulation of nonbasic types, such as spatial data types. We investigate the mapping of our reference model onto major commercial DBMS models, namely a relational model extended to abstract data types (ADT) and an object-oriented model. Our analysis shows the strengths and limits of the two model types for handling highly structured data with spatial components     

Modeling and querying moving objects in networks

Moving objects databases have become an important research issue in recent years. For modeling and querying moving objects, there exists a comprehensive framework of abstract data types to describe objects moving freely in the 2D plane, providing data types such as moving point or moving region. However, in many applications people or vehicles move along transportation networks. It makes a lot of sense to model the network explicitly and to describe movements relative to the network rather than unconstrained space, because then it is much easier to formulate in queries relationships between moving objects and the network. Moreover, such models can be better supported in indexing and query processing. In this paper, we extend the ADT approach by modeling networks explicitly and providing data types for static and moving network positions and regions. In a highway network, example entities corresponding to these data types are motels, construction areas, cars, and traffic jams. The network model is not too simplistic; it allows one to distinguish simple roads and divided highways and to describe the possible traversals of junctions precisely. The new types and operations are integrated seamlessly into the ADT framework to achieve a relatively simple, consistent and powerful overall model and query language for constrained and unconstrained movement.     

Spatio-Temporal Data Types: An Approach to Modeling and Querying Moving Objects in Databases

Spatio-temporal databases deal with geometries changing over time. In general, geometries cannot only change in discrete steps, but continuously, and we are talking about moving objects. If only the position in space of an object is relevant, then moving point is a basic abstraction; if also the extent is of interest, then the moving region abstraction captures moving as well as growing or shrinking regions. We propose a new line of research where moving points and moving regions are viewed as 3-D (2-D space+time) or higher-dimensional entities whose structure and behavior is captured by modeling them as abstract data types. Such types can be integrated as base (attribute) data types into relational, object-oriented, or other DBMS data models; they can be implemented as data blades, cartridges, etc. for extensible DBMSs. We expect these spatio-temporal data types to play a similarly fundamental role for spatio-temporal databases as spatial data types have played for spatial databases. The paper explains the approach and discusses several fundamental issues and questions related to it that need to be clarified before delving into specific designs of spatio- temporal algebras.     

时空数据库的发展与实现途径

从数据库结构的角度提出并比较了时空数据库的两种实现思路，肯定了在时态数据库中扩展空间数据属性实现时空数据库技术的优点及可行性。针对现有的某些理论研究比较成熟和总体实现模型较少的现状，介绍了实现时空数据库存在的问颢和难点所在。     

SQL extension for spatio-temporal data

An SQL extension is formalized for the management of spatio-temporal data, i.e. of spatial data that evolves with respect to time. The extension is dedicated to applications such as topography, cartography, and cadastral systems, hence it considers discrete changes both in space and in time. It is based on the rigid formalization of data types and of SQL constructs. Data types are defined in terms of time and spatial quanta. The SQL constructs are defined in terms of a kernel of few relational algebra operations, composed of the well-known operations of the 1NF model and of two more, Unfold and Fold. In conjunction with previous work, it enables the uniform management of 1NF structures that may contain not only spatio-temporal but also either purely temporal or purely spatial or conventional data. The syntax and semantics of the extension is fully consistent with the {SQL:2003} standard.     

时空数据库中多个最近邻对象的查询算法

在时空数据库中，最近邻查询用于对某个查询对象，在被查询对象中找出离它最近的一个或多个对象。该文在TPR树这一时空索引的基础上，提出了一种高效的最近邻查询算法，能够支持移动对象的多个最近邻对象的查询，并在性能上也有所提高。     

Designing a location update strategy for free-moving and network-constrained objects with varying velocity

Spatio-temporal databases aim at appropriately managing moving objects so as to support various types of queries. While much research has been conducted on developing query processing techniques, less effort has been made to address the issue of when and how to update location information of moving objects. Previous work shifts the workload of processing updates to each object which usually has limited CPU and battery capacities. This results in a tremendous processing overhead for each moving object. In this paper, we focus on designing efficient update strategies for two important types of moving objects, free-moving objects （FMOs） and network-constrained objects （NCOs）, which are classified based on object movement models. For FMOs, we develop a novel update strategy, namely the FMO update strategy （FMOUS）, to explicitly indicate a time point at which the object needs to update location information. As each object knows in advance when to update （meaning that it does not have to continuously check）, the processing overhead can be greatly reduced. In addition, the FMO update procedure （FMOUP） is designed to efficiently process the updates issued from moving objects. Similarly, for NCOs, we propose the NCO update strategy （NCOUS） and the NCO update procedure （NCOUP） to inform each object when and how to update location information. Exten- sive experiments are conducted to demonstrate the effectiveness and efficiency of the proposed update strategies.     

空间分析数据库的研究方法及技术

通过大量文献研究 ,分析了空间分析数据库的研究平台、研究方法和技术 ,以及各种研究平台的优缺点 .重点讨论了基于 Realms的空间数据类型、ROSE代数、基于可扩充 DBMS的空间分析数据库的研究方法和技术 ,以及同类系统的不足和需研究解决的问题 ,并指出 Realm s可以有效地表示二维的空间数据及支持空间拓扑操作算法 .文中还分析研究了基于主存数据库技术和 ROSE代数的空间存储管理子系统 ,并指出把它与可扩充数据库管理系统或具有 ADT机制的 DBMS进行集成 ,是研究空间分析 DBMS的有效途径