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PrefaceChapter 1 Introduction1£®1 Background1£®1£®1 Web service model and framework1£®1£®2 Web service composition definition1£®1£®3 Motivations and goals of Web service standards1£®2 Related standards and technologies1£®2£®1 Web service¡ªrelated standards and technologies1£®2£®2 Web service composition standards and technologies1£®2£®3 Sample for different standards supporting Web service composition1£®3 Web service composition methods1£®3£®1 Web service composition methods based on workflow1£®3£®2 Web service composition methods based on semantics1£®4 ReferencesChapter 2 Different Phases of web Service Composition2£®1 Composite process design2£®2 Deployment2£®3 Component service discovery2£®4 Component service selection2£®4£®1 Personal service selection2£®4£®2 Cooperative service selection2£®4£®3 Service selectionbased on QoS2£®5 Web service composition verification2£®5£®1 Requirements forverificationprocess2£®5£®2 Modelingthe compositionin MSCs2£®6 Composite Web service execution2£®6£®1 An example for execution of service composition2£®6£®2 Compatible executions2£®6£®3 Guaranteeing a composite service execution2£®7 ReferencesChapter 3 What is Component Service Optimization and Verificati on for Web Service Composition3£®1 Component service optimization3£®1£®1 Service optimization challenges3£®1£®2 Service optimization spectrum3£®1£®3 Optimization approaches3£®1£®4 Negotiation¡ªbased optimization3£®2 Verification of Web service composition3£®2£®1 Verification architecture3£®2£®2 Verification properties3£®2£®3 Operationalization correctness vefification3£®3 ReferencesChapter 4 A New Web Service Optimization with Memory CIassifier4£®1 Introduction4£®2 Fuzzy C¡ªmeans clustering algorithm£®4£®2£®1 Fuzzy C¡ªmeans fimctional4£®2£®2 Fuzzy C¡ªmeans clustering algorithm4£®2£®3 Parameters of the FCM algorithm4£®3 Artificial immune network4£®3£®1 Resource limited artificial immune system4£®3£®2 AiNet4£®3£®3 iNet4£®3£®4 IPAisys4£®4 Ontology¡ªoriented evaluation model description of semantic Web service based QoS4£®5 Evaluation algorithm of Web service based QoS4£®5£®1 The objective and subjective synthetic approach for weigh ofevaluation attribute4£®5£®2 Fuzzy C¡ªmeans artificial immune network memory classifier£¨FCMAINMC£©4£®6 Evaluation prototype system of Web service based QoS4£®7 Simulation4£®8 Conclusion4£®9 ReferencesChapter 5 Evaluation Model of Web Service Health Level on End¡ªto¡ªEnd Network Based on Artificial Immune5£®1 Introduction5£®2 Optimization using artificial immune svstems5£®3 ENHMM evaluation model construction5£®3£®1 Formation ofdynamic evaluation tree5£®3£®2 Evaluationdata acquiredbased on evaluationtree5£®3£®3 End¡ªto¡ªend network service health evaluation level designed5£®3£®4 Evaluation of network health level based on new aiNet immune network5£®4 ENHMM simulations5£®5 Conclusion5£®6 ReferencesChapter 6 Extended Evaluation for Quality of Service in the Community of Web Service6£®1 Introduction6£®2 Building Of Wleb service community6£®2£®1 Basic concepts6£®2£®2 Dynamic building of Web service community6£®3 Ontology¡ªoriented extended evaluation model description of semantic Web service6£®4 Triangular fuzzy analytic hierarchy process6£®4£®1 Triangular fuzzy numbers£¨TFNs£©6£®4£®2 Algebraic operations on TFNs6£®4£®3 Construction of the FAHP comparison matrices6£®4£®4 Value offuzzy synthetic extent6£®4£®5 Calculation of the sets ofweight values of the FAHP6£®5 A new evaluation algorithm based on triangular fuzzy number6£®5£®1 New triangular fuzzy analytic hierarchy process £¨NTFAHP£©6£®5£®2 Assessing of improved fuzzy comprehensive evaluation method6£®6 Evaluation examples6£®6£®1 Building of extended evaluation tree in the train booking service community6£®6£®2 Service evaluation6£®7 Conclusion6£®8 ReferencesChapter 7 Adaptive Evaluation and Selection of Information System by Triangular Fuzzy Number7£®1 Introduction7£®2 Reviews on information system evaluation theory7£®2£®1 User sarisfaction research stream7£®2£®2 Taxonomy framework of information system evaluation methods7£®3 A new information systems evaluation algorithm based on triangular fuzzy numbers7£®3£®1 Index of information system evaluation7£®3£®2 The weight obtained from NTFAHP7£®3£®3 Numerical examples7£®4 Framework of evaluation system7£®5 Discussion7£®6 Conclusion7£®7 ReferencesChapter 8 Service Selection of Ensuring Transactional Reliability and QoS for Web Service Composition8£®1 Introduction8£®2 Web service transaction descriptions8£®2£®1 Transactions overview8£®2£®2 Web service transactional property8£®213 Composite Web service transactional property8£®3 Transactional automaton services selection8£®3£®1 Workflow pa¡«erns8£®3£®2 Definition ofrisk tolerance8£®3£®3 Transactional automaton services selection8£®4 Transactional automaton model for services selection to Web service composition8£®4£®1 I£¯O automata8£®4£®2 Modelling transaction systems8£®4£®3 Transactional automaton model for services selection8£®4£®4 Example of service selection driven by transactional automaton model8£®5 QoS¡ªbased Web service selection8£®5£®1 QoS¡ªbased Web service model8£®5£®2 QOS¡ªbased composite Web service8£®5£®3 QoS¡ªbased service selection for CWS8£®6 Experimentation8£®7 Conclusion8£®8 ReferencesChapter 9 A Formal Transaction Model for Reliable Web Service Composition9£®1 Introduction9£®2 A formal description to Web services composition9£®3 Transaction model for WSC9£®3£®1 Transactional properties of Web service9£®3£®2 The set of controlflow andtransaction relationship9£®4 Generating of transaction relationship in the vorkgroup9£®4£®1 Complete set of TF9£®4£®2 Automatic generating of TF9£®4£®3 Validation of transaction model for Web service composition9£®5 Application of transaction model for Web service composition9£®6 Conclusion9£®7 References¡­¡­ Chapter 10 Reliable Execution Based on CPN and Skyline Optimization for Web Service CompositionChapter 11 Conformance Checking for Interaction of Web Service Composition with Temporal Logic