Moving Objects Management：Models,Techniques and Application（簡體書）

《移動對象管理:模型、技術與應用》內容簡介：隨著移動通信技術的不斷發展和普及，人們對移動對象管理的需求越來越迫切。移動對象管理成為數據庫研究領域的一個熱門方向，它在許多領域都展現了廣闊的應用前景。《移動對象管理:模型、技術與應用》比較系統地介紹了移動對象管理的相關內容，即移動對象管理模型（包括移動對象建模、移動對象更新、移動對象索引等），移動對象管理技術（包括移動對象查詢、移動對象預測、移動數據不確定性研究等），移動對象管理應用（包括動態交通導航、動態交通網絡、移動對象聚類分析、位置隱私保護等）。
《移動對象管理:模型、技術與應用》總結了國內外有關移動數據管理的研究工作和具有代表性的關鍵技術，并較詳細地介紹了作者近年來的一些研究成果，具有較大的參考價值。
《移動對象管理:模型、技術與應用》的讀者對象為高等院校計算機專業的本科生、研究生、教師，科研機構的研究人員以及相關領域的開發人員等。

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