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E-raamat: Grid Computing: Infrastructure, Service, and Applications

(Swinburne University of Technology), (University of Manchester, UK), (Rochester Institute of Technology, USA)
  • Formaat: 528 pages
  • Ilmumisaeg: 03-Oct-2018
  • Kirjastus: CRC Press Inc
  • Keel: eng
  • ISBN-13: 9781351834742
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Grid Computing: Infrastructure, Service, and ApplicationsSuurem pilt
  • Formaat: 528 pages
  • Ilmumisaeg: 03-Oct-2018
  • Kirjastus: CRC Press Inc
  • Keel: eng
  • ISBN-13: 9781351834742
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Identifies Recent Technological Developments Worldwide

The field of grid computing has made rapid progress in the past few years, evolving and developing in almost all areas, including concepts, philosophy, methodology, and usages. Grid Computing: Infrastructure, Service, and Applications reflects the recent advances in this field, covering the research aspects that involve infrastructure, middleware, architecture, services, and applications.

Grid Systems Across the Globe

The first section of the book focuses on infrastructure and middleware and presents several national and international grid systems. The text highlights China Research and Development environment Over Wide-area Network (CROWN), several ongoing cyberinfrastructure efforts in New York State, and Enabling Grids for E-sciencE (EGEE), which is co-funded by the European Commission and the worlds largest multidisciplinary grid infrastructure today.

The second part of the book discusses recent grid service advances. The authors examine the UK National Grid Service (NGS), the concept of resource allocation in a grid environment, OMIIBPEL, and the possibility of treating scientific workflow issues using techniques from the data stream community. The book describes an SLA model, reviews portal and workflow technologies, presents an overview of PKIs and their limitations, and introduces PIndex, a peer-to-peer model for grid information services.

New Projects and Initiatives

The third section includes an analysis of innovative grid applications. Topics covered include the WISDOM initiative, incorporating flow-level networking models into grid simulators, system-level virtualization, grid usage in the high-energy physics environment in the LHC project, and the Service Oriented HLA RTI (SOHR) framework.

With a comprehensive summary of past advances, this text is a window into the future of this nascent technology, forging a path for the next generation of cyberinfrastructure developers.
Foreword vii
Preface ix
Contributors xiii
Part I: Grid Infrastructure and Middleware 1
1. CROWN: A Service Grid Middleware for e-Science
3
Chunming Hu and Jinpeng Huai
1.1 Background
4
1.2 CROWN Middleware
5
1.2.1 Design Motivation
5
1.2.2 Architecture
6
1.2.3 Components in CROWN
8
1.2.3.1 Node Server
8
1.2.3.2 Resource Locating and Description Service (RLDS)
9
1.2.3.3 CROWN Scheduler
9
1.2.3.4 CROWN CommSec
9
1.2.3.5 CROWN AuthzService
9
1.2.3.6 CROWN CredMan
10
1.2.3.7 CROWN CredFed
10
1.2.3.8 CROWN ATN
10
1.2.3.9 CROWN Portal and Rich Client Framework
10
1.2.3.10 CROWN Designer
10
1.2.3.11 CROWN Monitor
10
1.2.4 Main Features
11
1.2.4.1 Overlay-Based Distributed Resource Management
12
1.2.4.2 Remote and Hot Deployment with Trust (ROST)
12
1.2.4.3 JSDL-Based Job Submission and BES-Based Job Scheduling
12
1.2.4.4 Security Architecture Supporting Domain Interoperability
13
1.3 Resource Management in CROWN
13
1.3.1 Overview
13
1.3.2 Node Server
13
1.3.3 S-Club and RCT
15
1.4 Security Architecture in CROWN
18
1.4.1 Overview of CROWN Security
18
1.4.1.1 Node-Level Security
19
1.4.1.2 Domain-Level Security
20
1.4.1.3 Region-Level Security
21
1.4.2 Design and Implementation
21
1.4.2.1 Security Structure for the CROWN Node
22
1.4.2.2 Communication Security
23
1.4.2.3 Policy-Based Authorization
24
1.4.2.4 Credential Management
24
1.4.2.5 Trust Management and Negotiation
25
1.4.2.6 Credential Federation
26
1.4.3 CROWN Security Summary
26
1.5 Testbed and Applications of CROWN
27
Acknowledgments
28
References
28
2. Cyberinfrastructure in New York State
31
Russ Miller, Jonathan J. Bednasz, Kenneth Chiu, Steven M. Gallo, Madhu Govindaraju, Michael Lewis, Catherine L. Ruby, and Charles M. Weeks
2.1 Introduction
32
2.2 Cyberinfrastructure in Buffalo
33
2.2.1 New York State Grid
33
2.2.2 Middleware Efforts
35
2.2.2.1 Grid Portal and Grid-Enabling Application Templates
35
2.2.2.2 Grid Monitoring and the Operations Dashboard
40
2.2.2.3 An Integrated Data and Computational Grid
42
2.2.2.4 Intelligent Grid Scheduling
42
2.3 Cyberinfrastructure in Binghamton
42
2.3.1 Optimizing Web and Grid Services
43
2.3.2 Optimizing SOAP
43
2.3.3 Binary XML
44
2.3.4 Uniform Dynamic Service Deployment
44
2.3.5 Benchmarking SOAP and XML
45
2.3.6 Component-Based Grid Computing
45
2.3.7 Grid-Enabled Instruments and Sensor Networks
46
2.3.8 Grid Emulation Framework for Multicore Processors
46
2.3.9 Protected Grid Data Transfer
47
2.4 New York State Cyberinfrastructure Initiative
47
2.4.1 Timeline
47
2.4.2 NYS Grid, Miller's Cyberinfrastructure Laboratory, and the Grassroots NYS Cyberinfrastructure Initiative
48
2.5 Final Remarks
51
Acknowledgments
52
References
52
3. Enabling Grids for e-Science: The EGEE Project
55
Erwin Laure and Bob Jones
3.1 Introduction
56
3.2 The EGEE Infrastructure
57
3.2.1 The EGEE Production Service
57
3.2.2 The Preproduction Service
61
3.2.3 Certification and Testing Testbeds
61
3.3 The gLite Middleware
62
3.4 EGEE Applications
65
3.4.1 Large Hadron Collider
66
3.4.2 The WISDOM Initiative
66
3.4.3 Digital Image Analysis
67
3.5 The Worldwide Grid Landscape
68
3.6 Future Work
70
3.7 Conclusions
72
Acknowledgments
72
References
72
4. ChinaGrid and Related Dependability Research
75
Xuanhua Shi and Hai Jin
4.1 Introduction
76
4.2 ChinaGrid Project: Vision and Mission
77
4.3 ChinaGrid Support Platform
78
4.3.1 Functions
79
4.3.2 Building Blocks
80
4.4 Grid Computing Application Platforms in the ChinaGrid
82
4.4.1 Bioinformatics Grid
82
4.4.1.1 Management of Heterogeneous Resources
83
4.4.1.2 Monitoring
83
4.4.1.3 Integration of Heterogeneous Bioinformatics Computing Tools
84
4.4.2 Image Grid
84
4.4.3 Computational Fluid Dynamics Grid
85
4.4.4 Course Online Grid
86
4.4.5 Massive Data Processing Grid
88
4.5 Grid Dependable Research
88
4.5.1 Grid Monitor
89
4.5.1.1 Architecture
89
4.5.1.2 Features
93
4.5.2 Fault Tolerant Grid Platform
93
4.5.2.1 Fault-Tolerant Grid Topology
94
4.5.2.2 Fault Tolerance of Information Server
95
4.5.2.3 Fault Tolerance of the System-Level Component
96
4.5.2.4 Task Fault Tolerance
96
4.5.3 Grid Fault Detection
101
4.5.3.1 Architecture
101
4.5.3.2 Adaptive Model
102
4.5.4 Adaptive Application Fault Tolerance
105
4.5.4.1 Overview of Failure Handling
106
4.5.4.2 Application-Level Fault-Tolerance Techniques
107
4.5.4.3 Model of Policy Making
108
4.6 Conclusion
113
Acknowledgments
113
References
113
5. Gridbus Workflow Enactment Engine
119
Jia Yu and Rajkumar Buyya
5.1 Introduction
120
5.2 Architecture
121
5.3 Workflow Execution Management
122
5.3.1 Communication Approach
123
5.3.2 State Transition
124
5.3.3 Interaction
125
5.4 Service Discovery
126
5.5 Workflow Language
128
5.5.1 Tasks
129
5.5.2 Data Dependencies
131
5.6 Parameterization
132
5.7 I/O Models
132
5.8 Fault Handling
134
5.9 Implementation
134
5.9.1 Design Diagram
134
5.9.2 Event Messages
135
5.10 A Case Study in fMRI Data Analysis
136
5.10.1 Population-Based Atlas Workflow
136
5.10.2 Experiment
138
5.11 Related Work
142
5.12 Summary
142
References
143
Part II: Grid Services 147
6. UK National Grid Service
149
Andrew Richards and Gillian M. Sinclair
6.1 Introduction
150
6.2 Background to the Creation of the NGS
150
6.3 Supporting the National Grid
151
6.4 National Grid Service Today
152
6.5 Core Founding Member Sites
154
6.6 Core Site Resources
154
6.6.1 Phase 1 Configuration
155
6.6.2 Phase 2 Configuration
155
6.7 National Grid Service Support Center
155
6.7.1 Core Services
156
6.7.1.1 Helpdesk
156
6.7.1.2 Certification Authority
156
6.7.1.3 Registration Authority
157
6.7.1.4 NGS Resources
157
6.7.1.5 User Support
157
6.7.1.6 Web Site
158
6.7.1.7 Training
158
6.7.1.8 NGS Portal
158
6.7.1.9 Documentation
159
6.7.1.10 User Account Management
159
6.7.1.11 Promotion, Outreach, and Education
160
6.7.1.12 Global Activities and Collaboration
160
6.7.2 Additional Services Provided by the NGS Support Center
160
6.7.2.1 Monitoring Services
160
6.7.2.2 GSI-SSH Terminal
161
6.7.2.3 MyProxy Upload Tool and MyProxy Server
161
6.7.2.4 NGS CPU Checking Utility
161
6.7.2.5 BDII MDS Service
162
6.7.2.6 Advanced Reservation
162
6.7.2.7 Wiki
162
6.7.2.8 Grid Operations Center DB
162
6.8 Partner- and Affiliate-Certified Sites
163
6.9 Documentation and Training
163
6.10 Future of the National Grid Service
165
6.11 Case Studies
165
6.11.1 Grid-Enabled Neurosurgical Imaging Using Simulation (GENIUS)
166
6.11.2 Modeling and Simulation for e-Social Science (MoSeS)
167
6.11.3 RTGrid
167
Acknowledgments
168
References
169
7. Grid Resource Allocation
171
Zhou Lei, Zhifeng Yun, and Gabrielle Allen
7.1 Introduction
172
7.2 Resource Allocation Needs
172
7.2.1 High-Throughput Computing
173
7.2.2 Resource Co-Allocation
173
7.2.3 Time-Critical Needs
174
7.2.4 Computing Synchronization
175
7.3 Resource Allocation Stages
176
7.3.1 Phase 1: Resource Discovery
176
7.3.2 Phase 2: System Selection
177
7.3.3 Phase 3: Job Submission
177
7.4 Major Approaches
177
7.4.1 Performance Prediction
177
7.4.1.1 Runtime Predictions
178
7.4.1.2 Queue Wait-Time Predictions
179
7.4.2 Resource Matching
179
7.4.3 Economic Scheduling
181
7.4.4 Peer-to-Peer Method
183
7.4.5 Advanced Reservation
185
7.5 Summary
187
Acknowledgments
188
References
188
8. Grid Services Orchestration with OMII-BPEL
191
Liang Chen, Wolfgang Emmerich, and Bruno Wassermann
8.1 Introduction
192
8.2 BPEL and Grid Service Orchestration
193
8.3 Interaction Modeling
194
8.4 Flow Control
198
8.5 Data Handling
200
8.6 Error Handling
201
8.7 Extensibility
202
8.8 Web Service Extensions
203
8.9 OMII-BPEL and BPEL Environment
203
8.10 Process Modeling and BPEL Designer
203
8.11 Usability
205
8.12 Validation
208
8.13 Server Runtime Integration
209
8.14 Simulation and Debug
209
8.15 Web Service Client
210
8.16 Process Enactment and ActiveBPEL
211
8.17 Deployment
211
8.18 Execution
212
8.19 Monitoring
215
8.20 Persistence
216
8.21 Security
217
8.22 A Polymorph-Search Case Study
217
8.23 Conclusions and Future Work
221
9. A Data Stream View of Scientific Workflow
223
Chi Yang and Jinjun Chen
9.1 Introduction
224
9.1.1 Research Scope of Scientific Workflow
225
9.1.2 Scientific Workflow on a Grid
225
9.1.3 Some Related Work on Scientific Workflow
225
9.1.4 Scientific Workflow Management by Database Management
227
9.1.4.1 Transactional and Objective Views of Workflows
227
9.1.4.2 How to Build up a WFMS with DBMS Views
229
9.1.5 Data Stream and Scientific Workflow
229
9.1.5.1 Data Stream Brevity
229
9.1.5.2 Data Stream View for Scientific Workflow
230
9.1.6 Measures for Scientific Workflow Management Systems
231
9.2 Stream View of Scientific Workflow Schema
232
9.2.1 Workflow Schema
232
9.2.2 Schema in DBMS and DSMS
233
9.2.3 XML Schema and Semistructured Data
233
9.2.3.1 Pattern Analysis of the XML Schema
234
9.3 Scientific Workflow and XML Data Streams
237
9.3.1 XML Data Streams Brevity
237
9.3.2 Event-Based Filtering Techniques
237
9.3.3 XML Data Stream View for Scientific Workflows
238
9.3.3.1 Similar Tree Pattern Schema
238
9.3.3.2 Automata for XML Streams and Scientific Workflow
239
9.3.3.3 Theoretic Lower Bounds for Scientific Workflow Scheduling
240
9.4 Scientific Workflow Runtime Scheduling and XML Stream Optimization
244
9.4.1 What is Optimization?
245
9.4.1.1 Static Optimization and Runtime Optimization
246
9.4.1.2 Semantic Optimization
246
9.4.2 Execution of Optimized Scientific Workflow
247
9.5 Conclusions and Future Work
248
References
248
10. Design of a Model-Based SLA Management Service and Its Applications over Distributed SOA Environments
253
Xiaorong Li, Subu Iyer, and Henry Palit
10.1 Introduction
254
10.2 Related Work
256
10.3 Architecture of an SLA Manager
257
10.3.1 SLA Manager and Its Environment
257
10.3.1.1 Definitions of the Roles
258
10.3.1.2 SLA Manager
259
10.3.1.3 Service Model Creation over the Shared Services Platform
260
10.3.1.4 CIM Models of SLA Manager
262
10.4 SLA Model and Its Implementation
263
10.4.1 SLA Model
263
10.4.2 SLA Negotiation and the Implementations
265
10.4.2.1 Retrieving SLA Templates
265
10.4.2.2 Proposing SLAs
265
10.4.2.3 Agreeing/Disagreeing to SLA
266
10.4.2.4 SLA Lifecycle
266
10.4.2.5 Management of SLA Copies
267
10.4.2.6 Signing the SLA Proposals
269
10.5 Applications of Fire Dynamic Simulation Services
270
10.5.1 Deployment for FDS Services with an SLA Manager
270
10.5.2 Performance Study
272
10.6 Conclusions
274
Acknowledgments
275
References
275
11. Portal and Workflow in Grid Computing: From Application Integration to Service Integration
279
Xiaoyu Yang
11.1 Introduction
280
11.2 Portals for Grid Application Integration
281
11.2.1 Portals and Portlets
281
11.2.1.1 Portals and Grid-Enabled Portals
281
11.2.1.2 Grid Portal: Nonportlet-Based versus Portlet-Based
282
11.2.1.3 Portlet Standards
282
11.2.2 Single Sign-On in Grid Portals
283
11.2.2.1 Globus Grid Security Infrastructure
283
11.2.2.2 Credential Management: MyProxy for Single Sign-On in Grid Portals
284
11.2.3 Portal in Grid Accounting
284
11.2.3.1 Related Work to Grid Accounting
285
11.2.3.2 Portal: Front-End of a Grid Accounting System
286
11.2.4 Integration of AJAX into Portal Application
287
11.2.5 Survey of Tools and Technologies for Grid-Enabled Portal Development
289
11.2.5.1 GridSphere
289
11.2.5.2 eXo Platform
289
11.2.5.3 Liferay Portal
290
11.2.5.4 Stringbeans
290
11.2.5.5 uPortal
290
11.2.5.6 Pluto
290
11.2.5.7 Jetspeed
291
11.2.5.8 Open Grid Computing Environment Toolkit
291
11.2.5.9 GridPort Toolkit
291
11.2.5.10 IBM WebSphere Portal
291
11.2.5.11 A Comparison Matrix of Grid Portal Tools and Technologies
292
11.3 Workflow to Integrate Services for Process Automation
292
11.3.1 Introduction to Workflow Technology
294
11.3.1.1 Service-Oriented Workflow
294
11.3.1.2 Workflow Languages
295
11.3.1.3 Workflow Engines
296
11.3.1.4 Workflow Systems
296
11.3.2 Workflows in Grid Computing
296
11.3.3 Start-of-the-Art: Service Component Architecture
297
11.4 A Case Study within the UK e-Science Program
299
11.4.1 UK e-Science Program
299
11.4.2 MaterialsGrid: Large-Scale Simulation of Physical Properties of Materials
300
11.4.3 MaterialsGrid Portal and Workflow System
301
11.5 Summary
302
Acknowledgments
303
References
303
12. Grid Security
307
Richard O. Sinnott
12.1 Introduction
308
12.2 Authentication and Grid Systems
309
12.2.1 Public Key Infrastructure
310
12.2.2 Problems with PKIs
311
12.3 Authorization and Grid Systems
312
12.3.1 Globus Security Infrastructure
313
12.3.2 Community Authorization Service
314
12.3.3 Virtual Organization Membership Service
315
12.3.4 Privilege and Role Management Infrastructure Standards Validation
316
12.4 Shibboleth and Grid Security
318
12.5 Case Studies in User-Oriented Grid Security
322
12.5.1 VOTES Project
323
12.5.2 GEMEPS Project
326
12.5.3 BRIDGES Project
328
12.6 Conclusions and Recommendations
329
References
331
13. Modeling P2P Grid Information Services with Colored Petri Nets
335
Vijay Sahota and Maozhen Li
13.1 Introduction
336
13.2 An Overview of Globus MDS4
337
13.3 PIndex for Scalable Grid Information Services
339
13.3.1 PIndex Architecture
340
13.3.2 Querying Resources in PIndex
341
13.4 Modeling PIndex with Colored Petri Nets
344
13.4.1 Existing Grid Simulators
345
13.4.1.1 SimGrid
345
13.4.1.2 GridSim
345
13.4.1.3 GangSim
345
13.4.1.4 CPN Tools Package
345
13.4.2 Choosing Colored Petri Nets for PIndex Modeling
346
13.4.3 Modeling PIndex with Colored Petri Nets
347
13.4.3.1 Model Design
347
13.4.3.2 Model Implementation
347
13.5 PIndex Evaluation Using Colored Petri Nets
348
13.5.1 Simulation Conditions
348
13.5.2 Simulation Results
350
13.6 Conclusion
353
References
354
Part III: Grid Applications 357
14. WISDOM: A Grid-Enabled Drug Discovery Initiative against Malaria
359
Vincent Breton, Doman Kim, and Giulio Rastelli
14.1 Introduction
360
14.2 Grid-Enabled Drug Discovery
360
14.2.1 In Silico Drug Discovery: Requirements and Grid Added Value
360
14.2.1.1 Requirements
362
14.2.1.2 Grid Added Value
363
14.2.2 Grid-Enabled Virtual Screening
365
14.2.2.1 The Virtual Screening Pipeline
365
14.3 Virtual Screening on the Grid: The WISDOM Initiative
367
14.3.1 Historical Perspective
367
14.3.2 First Data Challenge on Malaria
368
14.3.2.1 Preparation
368
14.3.2.2 Deployment
371
14.3.2.3 Results
372
14.3.3 Molecular Dynamics on the Grid
372
14.3.3.1 Introduction
372
14.3.3.2 Deployment
373
14.3.3.3 Molecular Dynamics Refinement and Rescoring Procedure
374
14.3.3.4 Results
376
14.3.4 In Vitro Tests
376
14.4 Second Data Challenge on Malaria
377
14.4.1 Introduction
377
14.4.2 Evolution of the Production Environment
379
14.4.3 Data Challenge Deployment
381
14.4.4 Postdocking Analysis and MD Refinement
382
14.5 Conclusion and Perspectives
383
Acknowledgments
385
References
386
15. Flow Networking in Grid Simulations
389
James Broberg and Rajkumar Buyya
15.1 Introduction
389
15.2 The GridSim Toolkit
391
15.3 The GridSim Packet Networking Architecture
392
15.4 Flow Networking Concepts
393
15.5 Bandwidth Sharing Models
394
15.6 The New GridSim Flow Networking Architecture
395
15.7 High-Level Flow Management Algorithms
398
15.8 Performance Comparison
399
15.9 Conclusion
402
Acknowledgments
403
References
403
16. Virtual Machines in Grid Environments: Dynamic Virtual Machines
405
Cong Du, Prerak Shukla, and Xian-He Sun
16.1 Introduction
406
16.1.1 Understanding System Virtualization
406
16.1.2 Technical Challenges
410
16.2 Recent Work in Virtual Machines for Grids
412
16.3 Dynamic Virtual Machine: The System Approach
413
16.3.1 Virtual Machine Modeling
416
16.3.2 VM Incarnation and Deployment
417
16.3.3 Virtual Machine Mobility
419
16.3.3.1 Runtime State Transfer
419
16.3.3.2 Communication State Transfer
420
16.3.3.3 Experimental Tests and Results
421
16.3.4 A Case Study of VM Modeling and Incarnation
421
16.3.5 DVM Mobility and Communication State Transfer
426
16.4 Conclusions and Future Work
428
References
429
17. High-Energy Physics Applications on the Grid
433
Massimo Lamanna
17.1 Introduction
433
17.2 The ARDA Project in LCG/EGEE
437
17.3 The LHC and the Grid Projects
439
17.4 HEP Analysis
441
17.5 The Dashboard and the Grid Reliability Tools
446
17.6 Data Management
452
17.6.1 Storage Resource Manager
452
17.6.2 File Transfer Service
452
17.6.3 Grid Catalogs
453
17.7 Conclusions
455
Acknowledgments
456
References
456
18. Design and Performance Evaluation of a Service-Oriented HLA RTI on the Grid
459
Ke Pan, Stephen John Turner, Wentong Cai, and Zengxiang Li
18.1 Introduction
460
18.2 Related Work
461
18.2.1 Grid-Facilitated Approach
461
18.2.2 Grid-Enabled Approach
463
18.2.3 Grid-Oriented Approach
464
18.3 Framework Overview of SOHR
464
18.4 Detailed Design of SOHR
467
18.4.1 Local RTI Component
467
18.4.2 Local Service
468
18.4.3 Federation Management Service
469
18.4.4 Declaration Management Service
469
18.4.5 Object and Ownership Management Service
470
18.4.6 Time Management Service
470
18.4.7 Data Distribution Management Service
471
18.4.8 RTI Index Service
471
18.5 Experiments and Results
472
18.5.1 Ping-Pong Experiment Design
472
18.5.2 Ping-Pong Experiment Trace on SOHR
472
18.5.3 Experimental Configurations and Results
475
18.6 Major Benefits of SOHR
477
18.7 Conclusions and Future Work
478
Acknowledgments
479
References
479
Index 483
Lizhe Wang, Wei Jie, Jinjun Chen
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