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Preface

Chapter 1 Introduction
1£®1 Background
1£®1£®1 Web service model and framework
1£®1£®2 Web service composition definition
1£®1£®3 Motivations and goals of Web service standards
1£®2 Related standards and technologies
1£®2£®1 Web service-related standards and technologies
1£®2£®2 Web service composition standards and technologies
1£®2£®3 Sample for different standards supporting Web service composition
1£®3 Web service composition methods
1£®3£®1 Web service composition methods based on workflow
1£®3£®2 Web service composition methods based on semantics
1£®4 References

Chapter 2 Different Phases of web Service Composition
2£®1 Composite process design
2£®2 Deployment
2£®3 Component service discovery
2£®4 Component service selection
2£®4£®1 Personal service selection
2£®4£®2 Cooperative service selection
2£®4£®3 Service selectionbased on QoS
2£®5 Web service composition verification
2£®5£®1 Requirements forverificationprocess
2£®5£®2 Modelingthe compositionin MSCs
2£®6 Composite Web service execution
2£®6£®1 An example for execution of service composition
2£®6£®2 Compatible executions
2£®6£®3 Guaranteeing a composite service execution
2£®7 References

Chapter 3 What is Component Service Optimization and Verificati on for Web Service Composition
3£®1 Component service optimization
3£®1£®1 Service optimization challenges
3£®1£®2 Service optimization spectrum
3£®1£®3 Optimization approaches
3£®1£®4 Negotiation-based optimization
3£®2 Verification of Web service composition
3£®2£®1 Verification architecture
3£®2£®2 Verification properties
3£®2£®3 Operationalization correctness vefification
3£®3 References

Chapter 4 A New Web Service Optimization with Memory CIassifier
4£®1 Introduction
4£®2 Fuzzy C-means clustering algorithm£®
4£®2£®1 Fuzzy C-means fimctional
4£®2£®2 Fuzzy C-means clustering algorithm
4£®2£®3 Parameters of the FCM algorithm
4£®3 Artificial immune network
4£®3£®1 Resource limited artificial immune system
4£®3£®2 AiNet
4£®3£®3 iNet
4£®3£®4 IPAisys
4£®4 Ontology-oriented evaluation model description of semantic Web service based QoS
4£®5 Evaluation algorithm of Web service based QoS
4£®5£®1 The objective and subjective synthetic approach for weigh ofevaluation attribute
4£®5£®2 Fuzzy C-means artificial immune network memory classifier£¨FCMAINMC£©
4£®6 Evaluation prototype system of Web service based QoS
4£®7 Simulation
4£®8 Conclusion
4£®9 References

Chapter 5 Evaluation Model of Web Service Health Level on End-to-End Network Based on Artificial Immune
5£®1 Introduction
5£®2 Optimization using artificial immune svstems
5£®3 ENHMM evaluation model construction
5£®3£®1 Formation ofdynamic evaluation tree
5£®3£®2 Evaluationdata acquiredbased on evaluationtree
5£®3£®3 End-to-end network service health evaluation level designed
5£®3£®4 Evaluation of network health level based on new aiNet immune network
5£®4 ENHMM simulations
5£®5 Conclusion
5£®6 References

Chapter 6 Extended Evaluation for Quality of Service in the Community of Web Service
6£®1 Introduction
6£®2 Building Of Wleb service community
6£®2£®1 Basic concepts
6£®2£®2 Dynamic building of Web service community
6£®3 Ontology-oriented extended evaluation model description of semantic Web service
6£®4 Triangular fuzzy analytic hierarchy process
6£®4£®1 Triangular fuzzy numbers£¨TFNs£©
6£®4£®2 Algebraic operations on TFNs
6£®4£®3 Construction of the FAHP comparison matrices
6£®4£®4 Value offuzzy synthetic extent
6£®4£®5 Calculation of the sets ofweight values of the FAHP
6£®5 A new evaluation algorithm based on triangular fuzzy number
6£®5£®1 New triangular fuzzy analytic hierarchy process £¨NTFAHP£©
6£®5£®2 Assessing of improved fuzzy comprehensive evaluation method
6£®6 Evaluation examples
6£®6£®1 Building of extended evaluation tree in the train booking service community
6£®6£®2 Service evaluation
6£®7 Conclusion
6£®8 References

Chapter 7 Adaptive Evaluation and Selection of Information System by Triangular Fuzzy Number
7£®1 Introduction
7£®2 Reviews on information system evaluation theory
7£®2£®1 User sarisfaction research stream
7£®2£®2 Taxonomy framework of information system evaluation methods
7£®3 A new information systems evaluation algorithm based on triangular fuzzy numbers
7£®3£®1 Index of information system evaluation
7£®3£®2 The weight obtained from NTFAHP
7£®3£®3 Numerical examples
7£®4 Framework of evaluation system
7£®5 Discussion
7£®6 Conclusion
7£®7 References

Chapter 8 Service Selection of Ensuring Transactional Reliability and QoS for Web Service Composition
8£®1 Introduction
8£®2 Web service transaction descriptions
8£®2£®1 Transactions overview
8£®2£®2 Web service transactional property
8£®213 Composite Web service transactional property
8£®3 Transactional automaton services selection
8£®3£®1 Workflow pa¡«erns
8£®3£®2 Definition ofrisk tolerance
8£®3£®3 Transactional automaton services selection
8£®4 Transactional automaton model for services selection to Web service composition
8£®4£®1 I£¯O automata
8£®4£®2 Modelling transaction systems
8£®4£®3 Transactional automaton model for services selection
8£®4£®4 Example of service selection driven by transactional automaton model
8£®5 QoS-based Web service selection
8£®5£®1 QoS-based Web service model
8£®5£®2 QOS-based composite Web service
8£®5£®3 QoS-based service selection for CWS
8£®6 Experimentation
8£®7 Conclusion
8£®8 References

Chapter 9 A Formal Transaction Model for Reliable Web Service Composition
9£®1 Introduction
9£®2 A formal description to Web services composition
9£®3 Transaction model for WSC
9£®3£®1 Transactional properties of Web service
9£®3£®2 The set of controlflow andtransaction relationship
9£®4 Generating of transaction relationship in the vorkgroup
9£®4£®1 Complete set of TF
9£®4£®2 Automatic generating of TF
9£®4£®3 Validation of transaction model for Web service composition
9£®5 Application of transaction model for Web service composition
9£®6 Conclusion
9£®7 References
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Chapter 10 Reliable Execution Based on CPN and Skyline Optimization for Web Service Composition
Chapter 11 Conformance Checking for Interaction of Web Service Composition with Temporal Logic