Focuses on how to use web service computing and service-based workflow technologies to develop timely, effective workflows for both business and scientific fields
Utilizing web computing and Service-Oriented Architecture (SOA), Business and Scientific Workflows: A Web ServiceOriented Approach focuses on how to design, analyze, and deploy web servicebased workflows for both business and scientific applications in many areas of healthcare and biomedicine. It also discusses and presents the recent research and development results.
This informative reference features application scenarios that include healthcare and biomedical applications, such as personalized healthcare processing, DNA sequence data processing, and electrocardiogram wave analysis, and presents:
- Updated research and development results on the composition technologies of web services for ever-sophisticated service requirements from various users and communities
- Fundamental methods such as Petri nets and social network analysis to advance the theory and applications of workflow design and web service composition
- Practical and real applications of the developed theory and methods for such platforms as personalized healthcare and Biomedical Informatics Grids
- The authors’ efforts on advancing service composition methods for both business and scientific software systems, with theoretical and empirical contributions
With workflow-driven service composition and reuse being a hot topic in both academia and industry, this book is ideal for researchers, engineers, scientists, professionals, and students who work on service computing, software engineering, business and scientific workflow management, the internet, and management information systems (MIS).
Table of Content
Foreword xi
Preface xiii
1. Introduction 1
1.1 Background and Motivations, 1
1.1.1 Web Service and Service-Oriented Architecture, 1
1.1.2 Workflow Technology, 4
1.2 Overview of Standards, 8
1.2.1 Web Service-Related Standards, 8
1.2.2 Workflow-Related Standards, 19
1.3 Workflow Design: State of the Art, 22
1.3.1 Automatic Service Composition, 22
1.3.2 Mediation-Aided Service Composition, 23
1.3.3 Verification of Service-Based Workflows, 24
1.3.4 Decentralized Execution of Workflows, 25
1.3.5 Scientific Workflow Systems, 26
1.4 Contributions, 27
2. Petri Net Formalism 29
2.1 Basic Petri Nets, 29
2.2 Workflow Nets, 32
2.3 Colored Petri Nets, 35
3. Data-Driven Service Composition 39
3.1 Problem Statement, 40
3.1.1 Domains and Data Relations, 41
3.1.2 Problem Formulation, 43
3.2 Data-Driven Composition Rules, 45
3.2.1 Sequential Composition Rule, 46
3.2.2 Parallel Composition Rule, 46
3.2.3 Choice Composition Rule, 47
3.3 Data-Driven Service Composition, 48
3.3.1 Basic Definitions, 48
3.3.2 Derive AWSP from Service Net, 50
3.4 Effectiveness and Efficiency of the Data-Driven Approach, 55
3.4.1 Solution Effectiveness, 55
3.4.2 Complexity Analysis, 56
3.5 Case Study, 57
3.6 Discussion, 60
3.7 Summary, 61
3.8 Bibliographic Notes, 62
4. Analysis and Composition of Partially-Compatible Web Services 65
4.1 Problem Definition and Motivating Scenario, 65
4.1.1 A Motivating Scenario, 68
4.2 Petri Net Formalism for BPEL Service, Mediation, and Compatibility, 70
4.2.1 CPN Formalism for BPEL Process, 70
4.2.2 CPN Formalism for Service Composition, 73
4.2.3 Mediator and Mediation-Aided Service Composition, 75
4.3 Compatibility Analysis via Petri Net Models, 78
4.3.1 Transforming Abstract BPEL Process to SWF-net, 79
4.3.2 Specifying Data Mapping, 80
4.3.3 Mediator Existence Checking, 81
4.3.4 Proof of Theorem 4.1, 85
4.4 Mediator Generation Approach, 88
4.4.1 Types of Mediation, 88
4.4.2 Guided Mediator Generation, 90
4.5 Bibliographic Notes, 94
4.5.1 Web Service Composition, 94
4.5.2 Business Process Integration, 94
4.5.3 Web Service Configuration, 94
4.5.4 Petri Net Model of BPEL Processes, 94
4.5.5 Component/Web Service Mediation, 95
5. Web Service Configuration with Multiple Quality-of-Service Attributes 99
5.1 Introduction, 99
5.2 Quality-of-Service Measurements, 104
5.2.1 Qo S Attributes, 104
5.2.2 Aggregation, 104
5.2.3 Computation of Qo S, 105
5.3 Assembly Petri Nets and Their Properties, 107
5.3.1 Assembly and Disassembly Petri Nets, 107
5.3.2 Definition of Incidence Matrix and State-Shift Equation, 110
5.3.3 Definition of Subgraphs and Solutions, 111
5.4 Optimal Web Service Configuration, 114
5.4.1 Web Service Configuration under Single Qo S Objective, 115
5.4.2 Web Service Configuration under Multiple Qo S Objectives, 116
5.4.3 Experiments and Performance Analysis, 117
5.5 Implementation, 121
5.6 Summary, 123
5.7 Bibliographic Notes, 124
6. A Web Service-Based Public-Oriented Personalized Health Care Platform 127
6.1 Background and Motivation, 127
6.2 System Architecture, 129
6.2.1 The System Architecture of PHISP, 129
6.2.2 Services Encapsulated in PHISP, 131
6.2.3 Composite Service Specifications, 133
6.2.4 User/Domain Preferences, 134
6.3 Web Service Composition with Branch Structures, 137
6.3.1 Basic Ideas and Concepts, 137
6.3.2 Service Composition Planner Supporting Branch Structures, 139
6.3.3 Illustrating Examples, 148
6.4 Web Service Composition with Parallel Structures, 153
6.5 Demonstrations and Results, 155
6.5.1 WSC Example in PHISP, 155
6.5.2 Implementation of PHISP, 158
6.6 Summary, 159
7. Scientific Workflows Enabling Web-Scale Collaboration 161
7.1 Service-Oriented Infrastructure for Science, 162
7.1.1 Service-Oriented Scientific Exploration, 162
7.1.2 Case Study: The Cancer Grid (ca Grid), 166
7.2 Scientific Workflows in Service-Oriented Science, 167
7.2.1 Scientific Workflow: Old Wine in New Bottle? 167
7.2.2 ca Grid Workflow Toolkit, 174
7.2.3 Exemplary ca Grid Workflows, 183
7.3 Summary, 188
8. Network Analysis and Reuse of Scientific Workflows 189
8.1 Social Computing Meets Scientific Workflow, 190
8.1.1 Social Network Services for Scientists, 191
8.1.2 Related Research Work, 197
8.2 Network Analysis of my Experiment, 199
8.2.1 Network Model at a Glance, 199
8.2.2 Undirected Network, 200
8.2.3 Directed Graph, 205
8.2.4 Summary of Findings, 206
8.3 Service Map: Providing Map and GPS Assisting Service Composition in Bioinformatics, 207
8.3.1 Motivation, 207
8.3.2 Service Map Approach, 209
8.3.3 What Do People Who Use These Services Also Use? 210
8.3.4 What is an Operation Chain Between Services/Operations, 212
8.3.5 An Empirical Study, 218
8.4 Summary, 219
9. Future Perspectives 221
9.1 Workflows in Hosting Platforms, 222
9.2 Workflows Empowered by Social Computing, 223
9.3 Workflows Meeting Big Data, 224
9.4 Emergency Workflow Management, 225
Abbreviations List 227
References 231
Index 247
About the author
WEI TAN, Ph D, is currently a Research Staff Member at IBM’s Thomas J. Watson Research Center. He received a Best Paper Award from the IEEE International Conference on Services Computing (2011), a Pacesetter Award from Argonne National Laboratory (2010), and ca BIG Teamwork Award from the National Cancer Institute (2008).
MENGCHU ZHOU, Ph D, is a Professor of Electrical and Computer Engineering and Director of the Discrete Event Systems Laboratory at the New Jersey Institute of Technology (NJIT). He is also a Professor at The Key Laboratory of Embedded System and Service Computing, Ministry of Education, Tongji University, Shanghai, China.
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