Smart Shadow: Models and Methods for Pervasive Computing

SmartShadow: Models and Methods for Pervasive Computing 

SmartShadow: Models and Methods for Pervasive Computing offers a new perspective on pervasive computing with SmartShadow, which is designed to model a user as a personality "shadow" and to model pervasive computing environments as user-centric dynamic virtual personal spaces. Just like human beings' shadows in the physical world, it follows people wherever they go, providing them with pervasive services. The model, methods, and software infrastructure for SmartShadow are presented and an application for smart cars is also introduced.
The book can serve as a valuable reference work for researchers and graduate students in the field of pervasive/ubiquitous computing.Zhaohui Wu is a Professor at Zhejiang University, Hangzhou, China.Gang Pan is a Professor at the same institute.

1 SmartShadow Model
1.1 Introduction
1.2 SmartShadow: An Overview
1.2.1 PersonalityShadow: Model of People's Life
1.2.2 ServiceShadow: User-Centered Virtual Space
1.3 Semantics in SmartShadow
1.3.1 Basic Concepts
1.3.2 Models and Systems in Pervasive Computing
1.3.3 Semantic Issues in SmartShadow
1.4 Modeling Human Personalities
1.4.1 Low-Level Personal Information
1.4.2 Mid-Level Personal Information
1.4.3 High-Level Personal Information: BDP Model
1.5 Modeling Computing Environments
1.6 Planning for a Virtual Service Space: ServiceShadow
1.7 Conclusion
References
2 Task Migration in SmartShadow
2.1 Introduction
2.2 Related Work
2.3 Task Migration Challenges
2.3.1 Scenario: Watching Movie
2.4 Task Model in SmartShadow
2.4.1 Modeling Task Process
2.4.2 Describing a Primitive Task
2.5 Context-Aware Task-to-Service Mapping
2.5.1 Semantic Service Filtering
2.5.2 Satisfaction Measurement for Task-Oriented Matching
2.5.3 Task-to-Service Mapping Algorithm
2.6 TaskShadow: An OSGi-Based Implementation
2.7 Evaluation
2.7.1 Performance of Task-to-Service Mapping
2.7.2 Time Cost for Task Migration of "Watch Movie".
2.8 Conclusion
References
3 Context-Awareness in SmartShadow
3.1 Introduction
3.2 Hierarchical Context Model
3.2.1 Context Atom Layer
3.2.2 Context Situation Layer
3.3 ScudContext: Large-Scale Environmental Context Services
3.3.1 Context Management
3.3.2 The ScudContext Infrastructure
3.4 ScudCORE: Context-Driven Reasoning Engine
3.4.1 Context-Driven Reasoning in Pervasive Computing
3.4.2 ScudCORE Architecture
3.4.3 Context-Driven Mechanism
3.5 Conclusion
References
4 File Modeling in SmartShadow
4.1 Introduction
4.2 Related Work
4.3 Modeling Files with Context Streams
4.3.1 Context Stream: Dynamics of Contexts
4.3.2 Modeling Files with Context Stream
4.4 ScudFile: A Meta File System with Context Streams
4.4.1 Architecture of the ScudFile
4.4.2 An MS-Windows-Based Implementation
4.5 Applications
4.5.1 File Browsing with Context Stream
4.5.2 File Searching with Context Stream
4.5.3 File Recommending with Context Stream
4.6 Evaluation
4.6.1 Time Cost
4.6.2 Usability Test
4.7 Conclusion
References
5 SeudWare: Software Infrastructure for SmartShadow
5.1 Introduction
5.2 ScudWare Architecture
5.3 Semantic Virtual Agents
5.3.1 SVA Definition
5.3.2 SIP Definition
5.4 Semantic Context Management Service
5.4.1 Semantic View for Context
5.4.2 Ontology of SmartShadow Space
5.4.3 Semantic Context Service Functional Modules
5.5 Adaptive Component Management Service
5.5.1 Resource Abstract
5.5.2 ACMS Functionality
5.5.3 Component Interdependence Graph
5.5.4 Run-Time Component Hook Proxy
5.6 Conclusion
References
6 Smart Car Space: An Application
6.1 Introduction
6.2 Smart Car Space: A Framework
6.3 Context Modeling in Smart Car Space
6.3.1 Context Atoms
6.3.2 Complex Context
6.4 Driver Behavior Modeling in Smart Car Space
6.4.1 Comfortable and Safe Driver Behavior Model of Car-Following
6.4.2 Multitasking Driver Behavior Model for Smart Car Space
6.5 Prototype
6.5.1 Network Infrastructure
6.5.2 Software Infrastructure
6.5.3 In-Car Space
6.5.4 Services of Smart Car Space
6.6 Conclusion
References
Index