Business and Scientific Workflows : a Web Service-Oriented Approach.
This reference book for system engineers, architects, and managers focuses on how to design, analyze, and deploy Web service-based workflows for both business and scientific applications in a broad domain of healthcare and biomedicine. It discusses recent research and development results, as well as...
| Κύριοι συγγραφείς: | , |
|---|---|
| Μορφή: | Ηλ. βιβλίο |
| Γλώσσα: | English |
| Έκδοση: |
Piscataway, NJ :
IEEE Press ;
[2013]
Hoboken, N.J. : Wiley, [2013] |
| Σειρά: | IEEE Press series on systems science and engineering.
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| Θέματα: | |
| Διαθέσιμο Online: | Full Text via HEAL-Link |
Πίνακας περιεχομένων:
- 1. Introduction; 1.1 Background and Motivations; 1.1.1 Web Service and Service-Oriented Architecture; 1.1.2 Workflow Technology; 1.2 Overview of Standards; 1.2.1 Web Service-Related Standards; 1.2.2 Workflow-Related Standards; 1.3 Workflow Design: State of the Art; 1.3.1 Automatic Service Composition; 1.3.2 Mediation-Aided Service Composition; 1.3.3 Verification of Service-Based Workflows; 1.3.4 Decentralized Execution of Workflows; 1.3.5 Scientific Workflow Systems; 1.4 Contributions.
- 2. Petri Net Formalism2.1 Basic Petri Nets; 2.2 Workflow Nets; 2.3 Colored Petri Nets.
- 3. Data-Driven Service Composition; 3.1 Problem Statement; 3.1.1 Domains and Data Relations; 3.1.2 Problem Formulation; 3.2 Data-Driven Composition Rules; 3.2.1 Sequential Composition Rule; 3.2.2 Parallel Composition Rule; 3.2.3 Choice Composition Rule; 3.3 Data-Driven Service Composition; 3.3.1 Basic Definitions; 3.3.2 Derive AWSP from Service Net; 3.4 Effectiveness and Efficiency of the Data-Driven Approach; 3.4.1 Solution Effectiveness; 3.4.2 Complexity Analysis; 3.5 Case Study; 3.6 Discussion; 3.7 Summary3.8 Bibliographic Notes.
- 4. Analysis and Composition of Partially-Compatible Web Services; 4.1 Problem Definition and Motivating Scenario; 4.1.1 A Motivating Scenario; 4.2 Petri Net Formalism for BPEL Service, Mediation, and Compatibility; 4.2.1 CPN Formalism for BPEL Process; 4.2.2 CPN Formalism for Service Composition; 4.2.3 Mediator and Mediation-Aided Service Composition; 4.3 Compatibility Analysis via Petri Net Models; 4.3.1 Transforming Abstract BPEL Process to SWF-net; 4.3.2 Specifying Data Mapping; 4.3.3 Mediator Existence Checking; 4.3.4 Proof of Theorem 4.1; 4.4 Mediator Generation Approach; 4.4.1 Types of Mediation; 4.4.2 Guided Mediator Generation; 4.5 Bibliographic Notes; 4.5.1 Web Service Composition; 4.5.2 Business Process Integration; 4.5.3 Web Service Configuration; 4.5.4 Petri Net Model of BPEL Processes; 4.5.5 Component/Web Service Mediation.
- 5. Web Service Configuration with Multiple Quality-of-Service Attributes; 5.1 Introduction; 5.2 Quality-of-Service Measurements; 5.2.1 QoS Attributes; 5.2.2 Aggregation; 5.2.3 Computation of QoS; 5.3 Assembly Petri Nets and Their Properties; 5.3.1 Assembly and Disassembly Petri Nets; 5.3.2 Definition of Incidence Matrix and State-Shift Equation5.3.3 Definition of Subgraphs and Solutions; 5.4 Optimal Web Service Configuration; 5.4.1 Web Service Configuration under Single QoS Objective; 5.4.2 Web Service Configuration under Multiple QoS Objectives; 5.4.3 Experiments and Performance Analysis; 5.5 Implementation; 5.6 Summary; 5.7 Bibliographic Notes.
- 6. A Web Service-Based Public-Oriented Personalized Health Care Platform; 6.1 Background and Motivation; 6.2 System Architecture; 6.2.1 The System Architecture of PHISP; 6.2.2 Services Encapsulated in PHISP; 6.2.3 Composite Service Specifications; 6.2.4 User/Domain Preferences; 6.3 Web Service Composition with Branch Structures; 6.3.1 Basic Ideas and Concepts; 6.3.2 Service Composition Planner Supporting Branch Structures; 6.3.3 Illustrating Examples; 6.4 Web Service Composition with Parallel Structures; 6.5 Demonstrations and Results; 6.5.1 WSC Example in PHISP; 6.5.2 Implementation of PHISP; 6.6 Summary.
- 7. Scientific Workflows Enabling Web-Scale Collaboration; 7.1 Service-Oriented Infrastructure for Science; 7.1.1 Service-Oriented Scientific Exploration; 7.1.2 Case Study: The Cancer Grid (caGrid); 7.2 Scientific Workflows in Service-Oriented Science; 7.2.1 Scientific Workflow: Old Wine in New Bottle?; 7.2.2 caGrid Workflow Toolkit; 7.2.3 Exemplary caGrid Workflows; 7.3 Summary.
- 8. Network Analysis and Reuse of Scientific Workflows; 8.1 Social Computing Meets Scientific Workflow; 8.1.1 Social Network Services for Scientists; 8.1.2 Related Research Work; 8.2 Network Analysis of myExperiment; 8.2.1 Network Model at a Glance; 8.2.2 Undirected Network; 8.2.3 Directed Graph; 8.2.4 Summary of Findings; 8.3 ServiceMap: Providing Map and GPS Assisting Service Composition in Bioinformatics; 8.3.1 Motivation; 8.3.2 ServiceMap Approach; 8.3.3 What Do People Who Use These Services Also Use?; 8.3.4 What is an Operation Chain Between Services/Operations; 8.3.5 An Empirical Study; 8.4 Summary.
- 9. Future Perspectives; 9.1 Workflows in Hosting Platforms; 9.2 Workflows Empowered by Social Computing; 9.3 Workflows Meeting Big Data; 9.4 Emergency Workflow Management.
