标题：移动对象管理：模型、技术与应用
图书信息
出版社: 清华大学出版社; 第1版 (2010年5月1日)
外文书名: Moving Objects Management:Models,Techniques and Applications
精装: 190页
正文语种: 英语
开本: 16
ISBN: 9787302223788, 7302223785
条形码: 9787302223788
尺寸: 24 x 16.2 x 1.6 cm
重量: 481 g
内容简介
《移动对象管理:模型、技术与应用》内容简介：随着移动通信技术的不断发展和普及，人们对移动对象管理的需求越来越迫切。移动对象管理成为数据库研究领域的一个热门方向，它在许多领域都展现了广阔的应用前景。《移动对象管理:模型、技术与应用》比较系统地介绍了移动对象管理的相关内容，即移动对象管理模型（包括移动对象建模、移动对象更新、移动对象索引等），移动对象管理技术（包括移动对象查询、移动对象预测、移动数据不确定性研究等），移动对象管理应用（包括动态交通导航、动态交通网络、移动对象聚类分析、位置隐私保护等）。
《移动对象管理:模型、技术与应用》总结了国内外有关移动数据管理的研究工作和具有代表性的关键技术，并较详细地介绍了作者近年来的一些研究成果，具有较大的参考价值。
《移动对象管理:模型、技术与应用》的读者对象为高等院校计算机专业的本科生、研究生、教师，科研机构的研究人员以及相关领域的开发人员等。
目录
Part I Moving Objects Management Models
Introduction
1.1  Background
1.1.1  Mobile Computing
1.1.2  Positioning Techniques
1.2  Location-Based Services
1.3  Mobile Data Management
1.4  Moving Object Databases
References
Moving Objects Modeling
2.1  Introduction
2.2  Underlying Models
2.3  Graphs of Cellular Automata Model
2.3.1  Cellular Automata (CA)
2.3.2  Structure of GCA
2.3.3  Trajectory of GCA
2.3.4  Transition of GCA
2.3.5  Two-Lane GCA
2.4  Summary
References
Moving Objects Updating
3.1  Introduction
3.2  Underlying Update Strategies
3.2.1  Based on Threshold
3.2.2  Based on Location Prediction
3.2.3  Based on Object Grouping
3.3  Proactive Location Update Strategy
3.4  Group Location Update Strategy
3.5  Summary
References
Moving Objects Indexing
4.1  Introduction
4.2  Underlying Indexing Structures
4.2.1  The R-Tree
4.2.2  The Grid File
4.2.3  The Quad-Tree
4.3  Indexing Moving Objects in Euclidean Space
4.3.1  The R-Tree-Based Index
4.3.2  The Grid-Based Index
4.3.3  The Quad-Tree-Based Index
4.4  Indexing Moving Objects in Spatial Networks
4.4.1  The Adaptive Unit
4.4.2  The Adaptive Network R-Tree (ANR-Tree)
4.5  Indexing Past, Present, and Future Trajectories
4.5.1  Indexing Future Trajectory
4.5.2  Indexing History Trajectories
4.6  Update-Efficient Indexing Structures
4.7  Summary
References
Part II Moving Objects Management Techniques
5   Moving Objects Basic Querying
5.1  Introduction
5.2  Classifications of Moving Object Queries
5.2.1  Based on Spatial Predicates
5.2.2  Based on Temporal Predicates
5.2.3  Based on Moving Spaces
5.3  NN Queries
5.3.1  Incremental Euclidean Restriction
5.3.2  Incremental Network Expansion
5.4  Range Queries
5.4.1  Range Euclidean Restriction
5.4.2  Range Network Expansion
5.5  Summary
References
Moving Objects Advanced Querying
6.1  Introduction
6.2  Similar Trajectory Queries for Moving Objects
6.2.1  Problem Definition
6.2.2  Trajectory Similarity
6.2.3  Query Processing
6.3  Density Queries for Moving Objects in Spatial Networks
6.3.1  Problem Definition
6.3.2  Cluster-Based Query Preprocessing
6.3.3  Density Query Processing
6.4  Continuous Density Queries for Moving Objects
6.4.1  Problem Definition
6.4.2  Building the Quad-Tree
6.4.3  Safe Interval Computation
6.4.4  Query Processing
6.5  Summary
References  ..
Trajectory Prediction of Moving Objects
7.1  Introduction
7.2  Underlying Linear Prediction (LP) Methods
7.2.1  General Linear Prediction
7.2.2  Road Segment-Based Linear Prediction ..
7.2.3  Route-Based Linear Prediction
7.3  Simulation-Based Prediction (SP) Methods
7.3.1  Fast-Slow Bounds Prediction
7.3.2  Time-Segmented Prediction
7.4  Other Non-Linear Prediction Methods
7.5  Summary
References
Uncertainty of Moving Objects
8.1  Introduction
8.2  Uncertain Trajectory Modeling
8.3  Uncertain Trajectory Indexing
8.3.1  Structure of the UTR-Tree
8.3.2  Construction and Maintenance of UTR-Tree
8.4  Uncertainty Trajectory Querying
8.5  Summary
References
Part III Moving Objects Management Applications
9   Dynamic Transportation Navigation
9.1  Introduction
9.2  Moving Objects Management Application Scenarios..
9.3  Dynamic Transportation Navigation
9.3.1  Hierarchy Aggregation Tree
9.3.2  Dynamic Navigation Query Processing
9.3.3  Dynamic Navigation System Architecture
9.4  Summary
References
10  Dynamic Transportation Networks
10.1 Introduction
10.2 The System Architecture
10.3 Data Model of Transportation Network and Moving Objects...
10.4 Querying Moving Objects in Transportation Networks
10.4.1 Computing the Locations Through Interpolation
10.4.2 Querying Moving Objects with Uncertainty
10.4.3 Location Prediction in Transportation Networks
10.5 Summary
References
11  Clustering Analysis of Moving Objects
11.1 Introduction
11.2 Underlying Clustering Analysis Methods
11.3 Clustering Static Objects in Spatial Networks
11.3.1 Problem Definition
11.3.2 Edge-Based Clustering Algorithm
11.3.3 Node-Based Clustering Algorithm
11.4 Clustering Moving Objects in Spatial Networks
11.4.1 CMON Framework
11.4.2 Construction and Maintenance of CBs
11.4.3 CMON Construction with Different Criteria
11.5 Summary
References
12  Location Privacy
12.1 Introduction
12.2 Privacy Threats in LBS
12.3 System Architecture
12.3.1 Non-Cooperative Architecture
12.3.2 Centralized Architecture
12.3.3 Peer-to-Peer Architecture
12.4 Location Anonyrnization Techniques
12.4.1 Location K-Anonymity Model
12.4.2 p-Sensitivity Model
12.4.3 Anonymization Algorithms
12.5 Evaluation Metrics
12.6 Summary
References
Index