Matching Semantic Service Capabilities

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Table of contents

1 Introduction 
1.1 Towards Service-Oriented Pervasive Computing
1.2 Thesis Contribution and Document Structure
2 Middleware for Service-Oriented Pervasive Computing: Vision and State Of The Art 
2.1 Pervasive Computing Environments
2.2 Service-Oriented Pervasive Computing
2.3 Middleware for Pervasive Computing Environments: State of The Art
2.3.1 Proprietary Middleware
2.3.2 Interoperable Middleware
2.3.3 Semantic-aware Middleware
2.3.4 Discussion
2.4 Semantic, Service-Oriented Middleware for Pervasive Computing
3 Semantic Specification of Pervasive Services 
3.1 Semantic Service Description Languages: State Of The Art
3.2 Semantic Service Specification Model
3.2.1 Provided and Required Capabilities
3.2.2 Conversation Specification
3.2.3 Non-functional Properties
3.3 Formalizing the Semantic Service Model
3.4 Concluding Remarks
4 Efficient Semantic Service Registry for Pervasive Computing Environments 
4.1 Efficient Semantic Service Matching: State Of The Art
4.1.1 Matching Semantic Service Capabilities
4.1.2 Cost of Semantic Service Matching
4.1.3 Optimizations to Semantic Service Matching
4.1.4 Discussion
4.2 Efficient Semantic Service Registry
4.2.1 Service Matching
4.2.2 Efficient Semantic Service Matching
4.2.3 Registry Service Index
4.2.4 Service Publication
4.2.5 Service Location
4.3 Assessing the Efficiency of the Semantic Service Registry
4.4 Concluding Remarks
5 Service Composition in Pervasive Computing Environments 
5.1 Service Composition: State Of The Art
5.1.1 Interface-Based Service Composition
5.1.2 Conversation-Based Service Composition
5.2 Semantic-, QoS-aware Conversation-driven Conversation Integration: Overview
5.3 Service Discovery Client
5.4 Service Conformance
5.4.1 Data Flow and Data Constraints
5.4.2 Ordering Constraints
5.5 Service Coordination
5.5.1 Problem Definition
5.5.2 Integrating Service Conversations
5.5.3 Support of Conversation Interleaving
5.5.4 Support of Adaptive User Tasks
5.6 Matching Global Non-Functional Properties of Composed User Tasks
5.7 On the fly User Task Realization for Meeting Pervasive Computing Requirements
5.8 Assessing the Efficiency of the Composition Model
5.9 Concluding Remarks
6 PERSE: Pervasive Semantic-aware Middleware 
6.1 Baseline MUSDAC Middleware for Multi-Network, Multi-Protocol Service
Discovery in Pervasive Computing Environments
6.2 The PERSE Middleware Architecture
6.2.1 Multi-Network Management
6.2.2 Service Discovery in PERSE
6.2.3 Service Composition in PERSE
6.2.4 Service Access in PERSE
6.2.5 Interoperable Service Description Language
6.3 Prototype Implementation and Performance Evaluation
6.3.1 Performance of the Prime Number-Based Ontology Encoding Algorithm
6.3.2 Cost of Legacy to ISDL Translation
6.3.3 Performance of the Interoperable Service Matching
6.3.4 Efficiency of the PERSE Service Registry
6.3.5 Performance of the QoS-Aware, Conversation-Based Service Com- position
7 Conclusion 
7.1 Contribution
7.2 Perspectives
A Proofs 
A.1 Proof of the property [Prop 1]
A.2 Proof of the property [Prop 2]
A.3 Proof of the property [Prop 3]
A.4 Proof of the transitivity of the relation FunctionalCapabilityMatch()
A.5 Proof of transitivity of the relation ConceptMatch()
A.6 Complexity of the ConversationMatch() relation
Bibliography