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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…mehr
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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:
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).
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).
Produktdetails
- Produktdetails
- Verlag: John Wiley & Sons
- Erscheinungstermin: 5. März 2013
- Englisch
- ISBN-13: 9781118554623
- Artikelnr.: 37757392
- Verlag: John Wiley & Sons
- Erscheinungstermin: 5. März 2013
- Englisch
- ISBN-13: 9781118554623
- Artikelnr.: 37757392
WEI TAN, PhD, 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 caBIG Teamwork Award from the National Cancer Institute (2008).
MENGCHU ZHOU, PhD, 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.
MENGCHU ZHOU, PhD, 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.
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 QoS Attributes, 104
5.2.2 Aggregation, 104
5.2.3 Computation of QoS, 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 QoS Objective, 115
5.4.2 Web Service Configuration under Multiple QoS 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 (caGrid), 166
7.2 Scientific Workflows in Service-Oriented Science, 167
7.2.1 Scientific Workflow: Old Wine in New Bottle? 167
7.2.2 caGrid Workflow Toolkit, 174
7.2.3 Exemplary caGrid 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 myExperiment, 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 ServiceMap: Providing Map and GPS Assisting Service Composition in Bioinformatics, 207
8.3.1 Motivation, 207
8.3.2 ServiceMap 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
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 QoS Attributes, 104
5.2.2 Aggregation, 104
5.2.3 Computation of QoS, 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 QoS Objective, 115
5.4.2 Web Service Configuration under Multiple QoS 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 (caGrid), 166
7.2 Scientific Workflows in Service-Oriented Science, 167
7.2.1 Scientific Workflow: Old Wine in New Bottle? 167
7.2.2 caGrid Workflow Toolkit, 174
7.2.3 Exemplary caGrid 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 myExperiment, 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 ServiceMap: Providing Map and GPS Assisting Service Composition in Bioinformatics, 207
8.3.1 Motivation, 207
8.3.2 ServiceMap 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
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 QoS Attributes
104 5.2.2 Aggregation
104 5.2.3 Computation of QoS
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 QoS Objective
115 5.4.2 Web Service Configuration under Multiple QoS 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 (caGrid)
166 7.2 Scientific Workflows in Service-Oriented Science
167 7.2.1 Scientific Workflow: Old Wine in New Bottle? 167 7.2.2 caGrid Workflow Toolkit
174 7.2.3 Exemplary caGrid 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 myExperiment
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 ServiceMap: Providing Map and GPS Assisting Service Composition in Bioinformatics
207 8.3.1 Motivation
207 8.3.2 ServiceMap 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
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 QoS Attributes
104 5.2.2 Aggregation
104 5.2.3 Computation of QoS
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 QoS Objective
115 5.4.2 Web Service Configuration under Multiple QoS 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 (caGrid)
166 7.2 Scientific Workflows in Service-Oriented Science
167 7.2.1 Scientific Workflow: Old Wine in New Bottle? 167 7.2.2 caGrid Workflow Toolkit
174 7.2.3 Exemplary caGrid 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 myExperiment
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 ServiceMap: Providing Map and GPS Assisting Service Composition in Bioinformatics
207 8.3.1 Motivation
207 8.3.2 ServiceMap 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
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 QoS Attributes, 104
5.2.2 Aggregation, 104
5.2.3 Computation of QoS, 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 QoS Objective, 115
5.4.2 Web Service Configuration under Multiple QoS 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 (caGrid), 166
7.2 Scientific Workflows in Service-Oriented Science, 167
7.2.1 Scientific Workflow: Old Wine in New Bottle? 167
7.2.2 caGrid Workflow Toolkit, 174
7.2.3 Exemplary caGrid 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 myExperiment, 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 ServiceMap: Providing Map and GPS Assisting Service Composition in Bioinformatics, 207
8.3.1 Motivation, 207
8.3.2 ServiceMap 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
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 QoS Attributes, 104
5.2.2 Aggregation, 104
5.2.3 Computation of QoS, 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 QoS Objective, 115
5.4.2 Web Service Configuration under Multiple QoS 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 (caGrid), 166
7.2 Scientific Workflows in Service-Oriented Science, 167
7.2.1 Scientific Workflow: Old Wine in New Bottle? 167
7.2.2 caGrid Workflow Toolkit, 174
7.2.3 Exemplary caGrid 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 myExperiment, 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 ServiceMap: Providing Map and GPS Assisting Service Composition in Bioinformatics, 207
8.3.1 Motivation, 207
8.3.2 ServiceMap 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
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 QoS Attributes
104 5.2.2 Aggregation
104 5.2.3 Computation of QoS
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 QoS Objective
115 5.4.2 Web Service Configuration under Multiple QoS 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 (caGrid)
166 7.2 Scientific Workflows in Service-Oriented Science
167 7.2.1 Scientific Workflow: Old Wine in New Bottle? 167 7.2.2 caGrid Workflow Toolkit
174 7.2.3 Exemplary caGrid 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 myExperiment
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 ServiceMap: Providing Map and GPS Assisting Service Composition in Bioinformatics
207 8.3.1 Motivation
207 8.3.2 ServiceMap 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
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 QoS Attributes
104 5.2.2 Aggregation
104 5.2.3 Computation of QoS
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 QoS Objective
115 5.4.2 Web Service Configuration under Multiple QoS 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 (caGrid)
166 7.2 Scientific Workflows in Service-Oriented Science
167 7.2.1 Scientific Workflow: Old Wine in New Bottle? 167 7.2.2 caGrid Workflow Toolkit
174 7.2.3 Exemplary caGrid 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 myExperiment
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 ServiceMap: Providing Map and GPS Assisting Service Composition in Bioinformatics
207 8.3.1 Motivation
207 8.3.2 ServiceMap 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