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Pervasive Computing

Book Description

This book introduces fundamental concepts and theories in pervasive computing as well as its key technologies and applications. It explains how to design and implement pervasive middleware and real application systems, covering nearly all aspects related to pervasive computing. Key technologies in the book include pervasive computing-oriented resource management and task migration, mobile pervasive transaction, human computer interface, and context collection-oriented wireless sensor networks.

Table of Contents

  1. Cover
  2. Half Title
  3. Title Page
  4. Copyright Page
  5. Table of Contents
  6. Preface
  7. About the Authors
  8. 1 Pervasive Computing Concepts
    1. 1.1 Perspectives of Pervasive Computing
      1. 1.1.1 Technology Trend Overview
      2. 1.1.2 Pervasive Computing: Concepts
    2. 1.2 Challenges
    3. 1.3 Technology
      1. 1.3.1 Middleware
      2. 1.3.2 Context Awareness
      3. 1.3.3 Resource Management
      4. 1.3.4 Human–Computer Interaction
      5. 1.3.5 Pervasive Transaction Processing
      6. 1.3.6 User Preference and Recommendations
    4. References
  9. 2 The Structure and Elements of Pervasive Computing Systems
    1. 2.1 Infrastructure and Devices
      1. 2.1.1 Wireless Networks
    2. 2.2 Middleware for Pervasive Computing Systems
      1. 2.2.1 Resource Management
      2. 2.2.2 User Tracking
      3. 2.2.3 Context Management
      4. 2.2.4 Service Management
      5. 2.2.5 Data Management
      6. 2.2.6 Security Management
    3. 2.3 Pervasive Computing Environments
      1. 2.3.1 Smart Car Space
      2. 2.3.2 Intelligent Campus
    4. Further Readings
    5. References
  10. 3 Context Collection, User Tracking, and Context Reasoning
    1. 3.1 Context Collection and Wireless Sensor Networks
      1. 3.1.1 Context Category
      2. 3.1.2 Context Collection Framework
    2. 3.2 User Tracking
      1. 3.2.1 Position Identification
      2. 3.2.2 Mobile Robot Position Identification
      3. 3.2.3 Intelligent Urban Traffic Management
    3. 3.3 Context Reasoning
      1. 3.3.1 Evidence Theory
      2. 3.3.2 DSCR Model
      3. 3.3.3 Propagating Evidence in the Sensors Layer
      4. 3.3.4 Propagating Evidence in the Objects Layer
      5. 3.3.5 Recognizing User Activity
      6. 3.3.6 Evidence Selection Strategy
      7. 3.3.7 Performance
    4. Further Readings
    5. References
  11. 4 Resource Management in Pervasive Computing
    1. 4.1 Efficient Resource Allocation in Pervasive Environments
      1. 4.1.1 Introduction to PMP Systems
      2. 4.1.2 Pipeline-Based Resource Allocation
      3. 4.1.3 Probabilistic Approach-Based Resource Allocation
        1. 4.1.3.1 Basic Algorithm
        2. 4.1.3.2 Optimized Algorithm
        3. 4.1.3.3 Probability Analysis
    2. 4.2 Transparent Task Migration
      1. 4.2.1 Introduction to Task Migration
      2. 4.2.2 Task Migration Model
        1. 4.2.2.1 HTML/DHTML Viewstate
        2. 4.2.2.2 OZ Source File Reorganization
        3. 4.2.2.3 Compiler Support
        4. 4.2.2.4 Application State Persistence and Recovery
      3. 4.2.3 Resource Redirection
        1. 4.2.3.1 Resource Handle Transformation Schema
        2. 4.2.3.2 Resource Transformation Schema
      4. 4.2.4 xMozart: A Novel Platform for Intelligent Task Migration
        1. 4.2.4.1 Migration Management Modules
        2. 4.2.4.2 Multiple Modalities
        3. 4.2.4.3 Multimodal Programming in xMozart
      5. 4.2.5 Implementation and Illustrations
        1. 4.2.5.1 Prototype for Application Migration
        2. 4.2.5.2 Prototype for Multimodalities
    3. Further Readings
    4. References
  12. 5 Human–Computer Interface in Pervasive Environments
    1. 5.1 Overview
    2. 5.2 HCI Service and Interaction Migration
    3. 5.3 Context-Driven HCI Service Selection
      1. 5.3.1 Interaction Service Selection Overview
      2. 5.3.2 User Devices
        1. 5.3.2.1 Service-Oriented Middleware Support
        2. 5.3.2.2 User History and Preference
      3. 5.3.3 Context Manager
      4. 5.3.4 Local Service Matching
      5. 5.3.5 Global Combination Selection
        1. 5.3.5.1 Effective Region
        2. 5.3.5.2 User Active Scope
        3. 5.3.5.3 Service Combination Selection Algorithm
    4. 5.4 Scenario Study: Video Calls at a Smart Office
      1. 5.4.1 Scenario Description
        1. 5.4.1.1 The Smart Office Environment
        2. 5.4.1.2 Scenario Description
      2. 5.4.2 HCI Migration Request
      3. 5.4.3 Context Format
      4. 5.4.4 Device Profile
      5. 5.4.5 Experiments and Results
        1. 5.4.5.1 Simulation Result
        2. 5.4.5.2 Scalability
    5. 5.5 A Web Service–Based HCI Migration Framework
      1. 5.5.1 HCI Migration Support Environment
      2. 5.5.2 Interaction Requirements Description
      3. 5.5.3 Interaction Devices Manager
      4. 5.5.4 Interaction Web Service
      5. 5.5.5 Runtime Migration Demonstration
    6. 5.6 Summary
    7. 5.7 Appendices
      1. 5.7.1 Request Format in XML
      2. 5.7.2 Context Format in XML
      3. 5.7.3 Device Profile in XML
    8. Further Readings
    9. References
  13. 6 Pervasive Mobile Transactions
    1. 6.1 Introduction to Pervasive Transactions
    2. 6.2 Mobile Transaction Framework
      1. 6.2.1 Unavailable Transaction Service
      2. 6.2.2 Pervasive Transaction Processing Framework
    3. 6.3 Context-Aware Pervasive Transaction Model
      1. 6.3.1 Context Model for Pervasive Transaction Processing
      2. 6.3.2 Context-Aware Pervasive Transaction Model
      3. 6.3.3 A Case of Pervasive Transactions
    4. 6.4 Dynamic Transaction Management
      1. 6.4.1 Context-Aware Transaction Coordination Mechanism
      2. 6.4.2 Coordination Algorithm for Pervasive Transactions
      3. 6.4.3 Participant Discovery
    5. 6.5 Formal Transaction Verification
      1. 6.5.1 Petri Net with Selective Transition
      2. 6.5.2 Petri Net–Based Formal Verification
    6. 6.6 Evaluations
      1. 6.6.1 Experiment Environment
      2. 6.6.2 Results and Evaluation
    7. Further Readings
    8. References
  14. 7 User Preferences and Recommendations
    1. 7.1 Content-Based Recommendation in an RSS Reader
      1. 7.1.1 Data Collection
      2. 7.1.2 Recommendation Features
      3. 7.1.3 Feature Combinations
      4. 7.1.4 Performance
    2. 7.2 A Collaborative Filtering-Based Recommendation
      1. 7.2.1 Background on Collaborative Filtering
      2. 7.2.2 CFSF Approach
        1. 7.2.2.1 Overview
        2. 7.2.2.2 Offline Phase
        3. 7.2.2.3 Online Phase
      3. 7.2.3 Performance of CFSF
        1. 7.2.3.1 Metrics
        2. 7.2.3.2 Overall Performance
    3. 7.3 Preference-Based Top-K Recommendation in Social Networks
      1. 7.3.1 Problem Formulation
      2. 7.3.2 Computing User Preferences
      3. 7.3.3 Greedy Algorithm for Mining Top-K Nodes
      4. 7.3.4 Performance
        1. 7.3.4.1 Influence Model
        2. 7.3.4.2 Algorithms and Metrics
        3. 7.3.4.3 Study on Influence Spread
        4. 7.3.4.4 ISST versus IS
        5. 7.3.4.5 Expert Search
        6. 7.3.4.6 GAUP versus CF
        7. 7.3.4.7 Topic Drift of HITS
    4. Further Readings
    5. References
  15. 8 Case Studies
    1. 8.1 iCampus Prototype
      1. 8.1.1 iShadow: Pervasive Computing Environment
      2. 8.1.2 Applications in iCampus Prototype
    2. 8.2 IPSpace: An IPv6-Enabled Intelligent Space
      1. 8.2.1 IPSpace Architecture Overview
        1. 8.2.1.1 Device Layer
        2. 8.2.1.2 Service Layer
        3. 8.2.1.3 Security Architecture
      2. 8.2.2 Lightweight Embedded Web Services
        1. 8.2.2.1 Middleware Layer
        2. 8.2.2.2 Implementation
      3. 8.2.3 Experiment
    3. Further Readings
    4. References
  16. Index