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Context-Aware Computing

Table of Contents

  1. Cover
  2. Title Page
  3. Copyright
  4. Dedication
  5. Preface
  6. Contents
  7. Acknowledgments
  8. Part I: Fundamental
    1. 1 Context-Aware Data Management Toward Ambient Intelligence
      1. 1.1 Ambient Intelligence
        1. 1.1.1 A Scenario
        2. 1.1.2 Challenges of Context-Awareness
      2. 1.2 What Is Context?
        1. 1.2.1 Context Definitions
        2. 1.2.2 Context Categorization
      3. 1.3 Characteristics of Context
        1. 1.3.1 Being Sensed
        2. 1.3.2 Through Constrained Devices
        3. 1.3.3 From Distributed Sources
        4. 1.3.4 Continuous Change
        5. 1.3.5 Mobility
        6. 1.3.6 Temporality and Spatiality
        7. 1.3.7 Imperfectness and Uncertainty
      4. 1.4 What Does Context-Awareness Imply?
        1. 1.4.1 Users’ Perspectives
        2. 1.4.2 Systems’ Perspectives
      5. 1.5 Context-Aware Querying
        1. 1.5.1 Basics of Context-Aware Queries
        2. 1.5.2 Context-Aware Querying Strategies
      6. 1.6 Supporting Context-Aware Data Management
        1. 1.6.1 Context Provider
        2. 1.6.2 Service Registry
        3. 1.6.3 Context Processor
        4. 1.6.4 Context Consumer
      7. 1.7 Recapitulation
      8. Literature
  9. Part II: Context
    1. 2 Modeling Context
      1. 2.1 Six Context Representation Methods
        1. 2.1.1 Key-Value
        2. 2.1.2 Entity-Relationship
        3. 2.1.3 Object-Orientation
        4. 2.1.4 Markup Schema
        5. 2.1.5 Logics
        6. 2.1.6 Ontology
        7. 2.1.7 Methods Comparison
      2. 2.2 Context Ontology
        1. 2.2.1 Context Formalism
        2. 2.2.2 Ontology Language – OWL
        3. 2.2.3 Logic Foundation of OWL – Description Logic (DL)
        4. 2.2.4 Correspondence Between OWL and DL
        5. 2.2.5 A Simple Context Ontology Example
      3. 2.3 Context Events
        1. 2.3.1 Interpreting Context as Context Events
        2. 2.3.2 Temporality of Context Events
        3. 2.3.3 Temporal Operators on Context Events
      4. 2.4 Recapitulation
      5. Literature
    2. 3 Addressing Context Uncertainty
      1. 3.1 Uncertainty
        1. 3.1.1 Aleatory Uncertainty
        2. 3.1.2 Epistemic Uncertainty
      2. 3.2 Uncertainty Processing Theories
        1. 3.2.1 Theory Overview
        2. 3.2.2 Probability Theory
        3. 3.2.3 Fuzzy Theory
        4. 3.2.4 Information-Gap Theory
        5. 3.2.5 Derived Uncertainty Theory
      3. 3.3 Uncertainty Processing Practices
        1. 3.3.1 Practice Overview
        2. 3.3.2 In Economics
        3. 3.3.3 In Engineering
        4. 3.3.4 In Ecology
        5. 3.3.5 In Information Science
        6. 3.3.6 In Databases
      4. 3.4 Context Uncertainty Management
        1. 3.4.1 Context Uncertainty
        2. 3.4.2 Probabilistic Context Events
        3. 3.4.3 Advanced Techniques of Context Uncertainty Management
      5. 3.5 Recapitulation
      6. Literature
    3. 4 Acquiring Context
      1. 4.1 Challenges in Context Acquisition
      2. 4.2 Three Context Acquisition Mechanisms
        1. 4.2.1 Offering Context Acquisition Services
        2. 4.2.2 Unifying Context Acquisition Interfaces
        3. 4.2.3 Building a General Context Provision and Acquisition Adaptor
      3. 4.3 A Declarative Specification Language for Context Acquisition
        1. 4.3.1 Point Descriptors
        2. 4.3.2 Connector Descriptors
        3. 4.3.3 Constraint Descriptors
        4. 4.3.4 Quality Descriptors
      4. 4.4 Quality-Assured Context Acquisition
        1. 4.4.1 The Least Squared Error of Redundant Context Values
        2. 4.4.2 Failure of Context Providers
      5. 4.5 Recapitulation
      6. Literature
    4. 5 Protecting Context Privacy
      1. 5.1 Balancing Privacy and Smartness
      2. 5.2 Privacy Protection Techniques
        1. 5.2.1 Access Control
        2. 5.2.2 Platform for Privacy Preferences (P3P)
        3. 5.2.3 Hippocratic Databases
        4. 5.2.4 Anonymity
        5. 5.2.5 Encryption
      3. 5.3 Search Over Encrypted XML Context Information
        1. 5.3.1 A Three-Phased Search Framework
        2. 5.3.2 Data Encoding Phase
        3. 5.3.3 Candidate Identification Phase
        4. 5.3.4 Tree Search Phase
      4. 5.4 Life-Cycle Management of Context Information
        1. 5.4.1 Requirements for Self-Regulation of Context Information
        2. 5.4.2 Limitations of Traditional Privacy Preservation Strategies
        3. 5.4.3 A Life-Cycle Policy (LCP) Model
        4. 5.4.4 Use Scenarios of LCPs
        5. 5.4.5 LCP-based Context Privacy Protection Diagram
        6. 5.4.6 Challenges with LCP-Based Privacy Protection
      5. 5.5 Recapitulation
      6. Literature
  10. Part III: Context Awareness
    1. 6 Querying Context
      1. 6.1 Seven Context Query Mechanisms
        1. 6.1.1 SQL Based
        2. 6.1.2 XML Based
        3. 6.1.3 Ontology Based
        4. 6.1.4 Event Based
        5. 6.1.5 Logic Based
        6. 6.1.6 Programming API Based
        7. 6.1.7 Graphic Interface Based
        8. 6.1.8 Mechanisms Comparison
      2. 6.2 Recapitulation
      3. Literature
    2. 7 Detecting Context Events
      1. 7.1 Integration of Stream and Event Processing
        1. 7.1.1 Stream and Event Processing Operators
        2. 7.1.2 Stream and Event Processing Methods
        3. 7.1.3 Stream and Event Processing Systems
      2. 7.2 High-Performance Context Event Detection
        1. 7.2.1 Indexing Stream Records
        2. 7.2.2 Condensed Composition of Stream Records
        3. 7.2.3 Partitioning Stream Records for Parallel Processing
      3. 7.3 Recapitulation
      4. Literature
    3. 8 Energy Management in Context Querying
      1. 8.1 Energy-Efficiency Requirement
      2. 8.2 Energy-Efficiency Problem
      3. 8.3 Solution Guidelines
      4. 8.4 Energy Management at Different Computing Levels
        1. 8.4.1 Energy-Efficient Hardware
        2. 8.4.2 Energy-Efficient Computer Systems
        3. 8.4.3 Energy-Efficient Cluster Systems
        4. 8.4.4 Energy-Efficient Applications
      5. 8.5 Models and Benchmarks of Energy Efficiency
        1. 8.5.1 Models and Metrics
        2. 8.5.2 Benchmarks
      6. 8.6 Energy-Efficient Query Processing and Optimization
        1. 8.6.1 Energy Management at Sensor Networks
        2. 8.6.2 Energy Management at Mobile Front Ends
        3. 8.6.3 Energy-Efficient Query Engines
      7. 8.7 Discussion
        1. 8.7.1 Redesigning Physical Context Database
        2. 8.7.2 Energy-Aware Query Processing and Optimization Strategies
        3. 8.7.3 Dynamic Workload and Resource Management
      8. 8.8 Recapitulation
      9. Literature
    4. 9 Context Query Efficiency Versus Expense
      1. 9.1 Basics of Cloud Computing
        1. 9.1.1 Service Models of Cloud Computing
        2. 9.1.2 Characteristics and Benefits of Cloud Computing
        3. 9.1.3 Key Benefits of Cloud Computing
      2. 9.2 Concerns of Context Query Performance and Expense
        1. 9.2.1 Performance Management
        2. 9.2.2 Resource Charging
      3. 9.3 Tuning of Query Performance and Expense
        1. 9.3.1 Problem Formulation
        2. 9.3.2 Multiple Objective Optimization
        3. 9.3.3 A Genetic Approach for Multiple Objective Optimization
        4. 9.3.4 Performance Evaluation
      4. 9.4 Recapitulation
      5. Literature
  11. Part IV: Context-Aware Data Management
    1. 10 Context-Aware Preference Querying
      1. 10.1 Query Preferences in Databases
        1. 10.1.1 Qualitative Representation of Preferences
        2. 10.1.2 Quantitative Representation of Preferences
      2. 10.2 Implanting Context-Aware Query Preferences upon a Relational Database Management System (RDBMS)
        1. 10.2.1 A Knowledge-Based Context-Aware Preference Model
        2. 10.2.2 Explicating Context-Aware Preferences in a Database World
        3. 10.2.3 Personalized Querying with Context-Aware Preferences
      3. 10.3 Contextual Ranking of Database Querying Results
        1. 10.3.1 A Motivation Example
        2. 10.3.2 Database and Context Space
        3. 10.3.3 Ranking Database Tuples Under Context Instances
        4. 10.3.4 Building Contextual Ranking Functions by Regression
        5. 10.3.5 Reducing Context Dimensionality in Contextual Ranking
      4. 10.4 Recapitulation
      5. Literature
    2. 11 Analyzing Sensitivity of Answer Ordering Change
      1. 11.1 Motivation
      2. 11.2 Sensitivity Analysis Techniques in Databases
        1. 11.2.1 Attribute Selection
        2. 11.2.2 Provenance and Lineage
        3. 11.2.3 Causality and Responsibility
        4. 11.2.4 Sensitivity Measurement and Computation
      3. 11.3 Sensitivity Analysis Problem for Answer Ordering Change
        1. 11.3.1 Review of the Probabilistic Database Model
        2. 11.3.2 Answer Ordering Change
        3. 11.3.3 Measurement of Answer Ordering Change
        4. 11.3.4 Sensitivity of Answer Ordering Change
      4. 11.4 Sensitivity Computation for Answer Ordering Change
        1. 11.4.1 Five Computation Modules
        2. 11.4.2 Sensitivity Computation Method
        3. 11.4.3 Performance
      5. 11.5 Recapitulation
      6. Literature
    3. 12 Explaining and Scrubbing Context-Aware Query Results
      1. 12.1 Motivation
      2. 12.2 Result Explanation and Uncertain Data Cleaning Techniques
        1. 12.2.1 Explanation in General
        2. 12.2.2 Explanation in Databases
        3. 12.2.3 User Feedback
        4. 12.2.4 Cleaning Data Uncertainty
      3. 12.3 Design Principles for Answer Explanation Facility
      4. 12.4 Involving Users in Querying Uncertain Context Data
        1. 12.4.1 Result Explanation
        2. 12.4.2 Query Recomputation
        3. 12.4.3 Performance
        4. 12.4.4 Discussion
      5. 12.5 Recapitulation
      6. Literature
    4. 13 Context-Based Information Refinding
      1. 13.1 Characteristics of Information Refinding
        1. 13.1.1 Refinding Is a Common Activity
        2. 13.1.2 Differences from Information Finding
        3. 13.1.3 Difficulties in Information Refinding
      2. 13.2 Overview of Information Refinding Techniques
        1. 13.2.1 Web Information Refinding
        2. 13.2.2 Personal Information Refinding
        3. 13.2.3 Comparison of Different Refinding Techniques
      3. 13.3 Nature-Inspired Context-Based Refinding
        1. 13.3.1 Brain’s Memory Recall
        2. 13.3.2 Information Refinding by Structured Context
        3. 13.3.3 Web Revisitation by Context and Content Keywords
      4. 13.4 Recapitulation
      5. Literature
  12. Part V: Context-Aware Applications
    1. 14 A Context-Aware Ad-Hoc Meeting Planner Program
      1. 14.1 Early Pioneering Context-Aware Applications
      2. 14.2 Motivation
      3. 14.3 Context-Awareness in ConPlan
      4. 14.4 ConPlan Design Considerations
      5. 14.5 ConPlan Framework
      6. 14.6 ConPlan Context Management
      7. 14.7 ConPlan Implementation
      8. 14.8 Recapitulation
      9. Literature
    2. 15 Context-Aware Learning
      1. 15.1 Learning in an Ambient Intelligent World
      2. 15.2 Motivation of Context-Aware Learning
      3. 15.3 Five Kinds of Learning Context
      4. 15.4 Enabling Techniques for Context-Aware Learning
        1. 15.4.1 GPS-based Learning
        2. 15.4.2 Sensor-Based Learning
        3. 15.4.3 Personalized Learning
        4. 15.4.4 RFID-based Learning
      5. 15.5 Some Context-Aware Learning Prototypes
      6. 15.6 Challenges upon Context-Aware Learning
      7. 15.7 Recapitulation
      8. Literature
    3. 16 Context-Aware Management of Bilingual Aviation MRO Task Cards
      1. 16.1 Motivation
      2. 16.2 Generating Bilingual MRO Task Cards (TaskCardGeneratore2c)
        1. 16.2.1 TaskCardGeneratore2c Architecture
        2. 16.2.2 TaskCardGeneratore2c Implementation
      3. 16.3 Searching Bilingual MRO Task Cards (TaskCardFinder)
        1. 16.3.1 Existing Search Engines
        2. 16.3.2 TaskCardFinder Functionalities
        3. 16.3.3 TaskCardFinder Architecture
        4. 16.3.4 TaskCardFinder Implementation
      4. 16.4 User Study
        1. 16.4.1 On TaskCardGeneratore2c
        2. 16.4.2 On TaskCardFinder
      5. 16.5 Recapitulation
      6. Literature
    4. 17 FireVGuide: A Context-Aware Fire Victims Guide
      1. 17.1 Motivation
        1. 17.1.1 Two Real Fire Disasters
        2. 17.1.2 Reflection of the Real Fire Disasters
        3. 17.1.3 Necessity of FireVGuide
        4. 17.1.4 Assumptions of FireVGuide
        5. 17.1.5 Principles of FireVGuide
      2. 17.2 State-of-Art Firefighting Techniques
        1. 17.2.1 Supporting Firefighters
        2. 17.2.2 Supporting Fire Victims
      3. 17.3 Solution Requirements
        1. 17.3.1 Building Structure
        2. 17.3.2 Timeliness
        3. 17.3.3 Simple Interaction
        4. 17.3.4 Reliability
      4. 17.4 FireVGuide Architecture
        1. 17.4.1 Hardware Deployment
        2. 17.4.2 Software Architecture
      5. 17.5 FireVGuide Guidance Generation
        1. 17.5.1 Evacuation Route Generation
        2. 17.5.2 To-Do-List Generation for Trapped Occupants
      6. 17.6 Evaluation of FireVGuide
        1. 17.6.1 User Interviews
        2. 17.6.2 Empirical Experience with FireVGuide
        3. 17.6.3 Effectiveness of FireVGuide
        4. 17.6.4 Efficiency of FireVGuide
      7. 17.7 Recapitulation
      8. Literature
  13. Index