Fundamentals of grid computing: theory, algorithms and technologies
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| Format: | Book |
|---|---|
| Language: | English |
| Published: |
Boca Raton, Fla. [u.a.]
CRC Press
2010
|
| Series: | Chapman & Hall/CRC numerical analysis and scientific computing
|
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Physical Description: | XXI, 298 S. Ill., graph. Darst. |
| ISBN: | 9781439803677 |
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MARC
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| 245 | 1 | 0 | |a Fundamentals of grid computing |b theory, algorithms and technologies |c ed. by Frédéric Magoulès |
| 264 | 1 | |a Boca Raton, Fla. [u.a.] |b CRC Press |c 2010 | |
| 300 | |a XXI, 298 S. |b Ill., graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
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Record in the Search Index
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| adam_text |
Contents
List of figures
xiii
List of tables
xvii
Foreword
xix
Preface
xxi
Warranty
xxiii
1
Grid computing overview
1
Frédéric Magoulès,
Thi-Mai-Huong
Nguyen, and Lei Yu
1.1
Introduction
. 1
1.2
Definitions
. 2
1.3
Classifying grid systems
. 3
1.4
Grid applications
. 4
1.5
Grid architecture
. 5
1.6
Grid computing projects
. 6
1.6.1
Grid middleware (core services)
. 6
1.6.2
Grid resource brokers and schedulers
. 11
1.6.3
Grid systems
. 14
1.6.4
Grid programming environments
. 16
1.6.5
Grid portals
. 18
1.7
Grid evolution
. 22
1.8
Concluding remarks
. 23
1.9
References
. 24
2
Synchronization protocols for sharing resources in grid envi¬
ronments
29
Julien
Sopeña, Luciana Arantes,
Fabrice
Legond-Aubry, and Pierre Sens
2.1
Introduction
. 29
2.2
Token-based mutual exclusion algorithms
. 31
2.2.1
Martin's algorithm
. 31
2.2.2
Naimi-Tréheľs
algorithm
. 33
2.2.3
Suzuki-Kasami's algorithm
. 34
2.3
Mutual exclusion algorithms for large configurations
. 36
2.3.1
Priority-based approach
. 36
vii
Vlil
2.3.2
Composition-based approach
. 37
2.4
Composition approach to mutual exclusion algorithms
. 39
2.4.1
Coordinator processes
. 41
2.5
Composition properties and its natural effects
. 43
2.5.1
Filtering and aggregation
. 43
2.5.2
Preemption and structural effects
. 45
2.5.3
Natural effects of composition
. 46
2.6
Performance evaluation
. 47
2.6.1
Experiment parameters
. 47
2.6.2
Performance results: composition study
. 49
2.6.3
The impact of the grid architecture
. 56
2.7
Concluding remarks
. 62
2.8
References
. 63
3
Data replication in grid environments
67
Thi-Mai-Huong Nguyen and
Frédéric Magoulès
3.1
Introduction
. 67
3.2
Data replication
. 68
3.2.1
Replication in databases
. 69
3.2.2
Replication in peer-to-peer systems
. 70
3.2.3
Replication in web environments
. 71
3.2.4
Replication in data grids
. 72
3.3
System architecture
. 76
3.4
Selective-rank model for a replication system
. 78
3.4.1
Model assumptions
. 79
3.4.2
Estimating the availability of files
. 80
3.4.3
Problem definition
. 80
3.5
Selective-rank replication algorithm
. 82
3.5.1
Popularity of files
. 82
3.5.2
Correlation of files
. 82
3.5.3
MaxDAR optimizer algorithm
. 83
3.6
Evaluation
. 85
3.6.1
Grid configuration
. 87
3.6.2
Experimental results
. 87
3.7
Concluding remarks
. 94
3.8
References
. 95
4
Data management in grids
101
Jean-Marc Pierson
4.1
Introduction
. 101
4.2
From data sources to databases
.
to data sources
. 103
4.3
Positioning the data management in grids within distributed
systems
. 104
4.4
Links with the other services of the middleware
. 106
4.5
Problems and some solutions
.■. 107
4.5.1
Data identification, indexing, metadata
. 107
4.5.2
Data access, interoperability, query processing, transac¬
tions
. 109
4.5.3
Transport
.
Ш
4.5.4
Placement, replication, caching
. 112
4.5.5
Security: transport, authentication, access control, en¬
cryption
. 113
4.5.6
Consistency
. 115
4.6
Toward pervasive,
autonomie
and on-demand data manage¬
ment
. 116
4.7
Concluding remarks
. 117
4.8
References
. 118
5
Future of grids resources management
125
Fei
Teng
and
Frédéric Magoulès
5.1
Introduction
. 125
5.2
Several computing paradigms
. 126
5.2.1
Utility computing
. 126
5.2.2
Grid computing
. 127
5.2.3
Autonomie
computing
. 127
5.2.4
Cloud computing
. 128
5.3
Definition of cloud computing
. 129
5.3.1
One definition
. 129
5.3.2
Architecture
. 130
5.4
Cloud services
. 130
5.4.1
Three-level services
. 130
5.4.2
Service characters
. 132
5.5
Cloud resource management
. 134
5.5.1
Comparison with grid systems
. 134
5.5.2
Resource model
. 135
5.5.3
Economy-oriented model
. 136
5.6
Future direction of resource scheduling
. 137
5.6.1
Scalable and dynamic
. 138
5.6.2
Secure and trustable
. 138
5.6.3
Virtual machines-based
. 138
5.7
Concluding remarks
. 139
5.8
References
. 140
6
Fault-tolerance and availability awareness in computational
grids
143
Xavier
Besseren, Mohamed-Slim Bouguerra,
Thierry
Gautier, Erik Saule,
and Denis Trystram
6.1
Introduction
. 143
6.2
Background and definitions
. 146
6.2.1
Grid architecture and execution model
. 147
6.2.2
Faults models
. 148
6.2.3
Consistent system states
. 148
6.3
Multi-objective scheduling for safety
. 149
6.3.1
Generalities
. 149
6.3.2
No duplication
. 150
6.3.3
Using duplication
. 152
6.4
Stable memory-based protocols
. 153
6.4.1
Log-based rollback recovery
. 153
6.4.2
Checkpoint-based rollback recovery
. 155
6.5
Stochastic checkpoint model analysis issues
. 156
6.5.1
Completion time without fault tolerance
. 157
6.5.2
Impact of checkpointing on the completion time
. . . 159
6.6
Implementations
. 163
6.6.1
Single process snapshot
. 164
6.6.2
Fault-tolerance protocol implementations
. 164
6.6.3
Implementation comparison
. 166
6.7
Concluding remarks
. 168
6.8
References
. 170
7
Fault tolerance for distributed scheduling in grids
177
Lei Yu and
Frédéric Magoules
7.1
Introduction
. 177
7.2
Fault tolerance in distributed systems
. 179
7.3
Distributed scheduling model
. 180
7.3.1
MMS
fault tolerance
. 180
7.3.2
LMS/SMS fault tolerance
. 181
7.3.3
CR fault tolerance
. 182
7.4
Fault detection and repairing in the tree structure
. 183
7.4.1
Notations
. 183
7.4.2
Algorithms description
. 183
7.4.3
Messages treatment analysis
. 188
7.5
Distributed scheduling algorithm
. 189
7.5.1
Distributed dynamic scheduling algorithm with fault
tolerance (DDFT)
. 189
7.5.2
Algorithm fault tolerance issues
. 190
7.6
SimGrid and simulation design
. 191
7.7
Evaluation
. 192
7.7.1
Simulation setup
. 193
7.7.2
Comparison with centralized scheduling
. 193
7.7.3
Fault tolerance experiments
. 197
7.7.4
Workload analysis
. 197
7.8
Related work
. 199
7.9
Concluding remarks
. 200
7.10
References
. 201
Xl
Broadcasting for grids
207
Christophe
Cérin,
Luiz-Angelo Steffenel, and Hazem Fkaier
8.1
Introduction
. 207
8.2
Broadcastings
. 208
8.3
Heuristics for broadcasting
. 211
8.3.1
Basic approaches for broadcasting in homogeneous en¬
vironments
. 212
8.3.2
Advanced approaches for heterogeneous clusters
. . . 213
8.3.3
Grid aware heuristics
. 214
8.3.4
New approach for broadcasting in clusters and hyper
clusters
. 215
8.4
Related work and related methods
. 220
8.4.1
Broadcasting and dynamic programming
. 220
8.4.2
Multi-criteria approach
. 223
8.4.3
Broadcast for clusters
. 228
8.4.4
Broadcast and heterogeneous systems
. 230
8.5
Concluding remarks
. 230
8.6
References
. 232
Load balancing algorithms for dynamic networks
235
Jacques M. Bahi,
Raphaël
Couturier, and Abderrahmane Sider
9.1
Introduction
. 235
9.2
A taxonomy for load balancing
. 237
9.3
Distributed load balancing algorithms for static networks
. . 240
9.3.1
Network model and performance measures
. 240
9.3.2
Diffusion
. 242
9.3.3
Dimension exchange
. 246
9.3.4
GDE
. 248
9.3.5
Second order algorithms
. 250
9.4
Distributed load balancing algorithms for dynamic networks
250
9.4.1
Adaption to dynamic networks
. 251
9.4.2
Generalized adaptive exchange (GAE)
. 251
9.4.3
Illustrating the generalized adaptive exchange most to
least loaded policy on a dynamic network
. 255
9.5
Implementation
. 257
9.5.1
On synchronous and asynchronous approaches
. 257
9.5.2
How to define the load for some applications
. 259
9.5.3
Implementation of static algorithms
. 259
9.5.4
Implementation of dynamic algorithms
. 260
9.6
A practical example: the advection diffusion application
. . . 261
9.6.1
Load balancing and the application
. 264
9.6.2
Load balancing in a dynamic network
. 266
9.7
Concluding remarks
. 268
9.8
References
. 269
от
A
Implementation
of the replication strategies in OptorSim
273
Thi-Mai-Huong Nguyen and
Frédéric Magoulès
A.I Introduction
. 273
A.2 Download
. 274
A.3 Implementation
. 274
A.3.1 OptorSim implementation
. 274
A.3.2 MaxDAR implementation
. 275
A.4 How to execute the simulation
. 276
В
Implementation of the simulator for the distributed schedul¬
ing model
279
Lei Yu and
Frédéric Magoulès
B.I Introduction
. 279
B.2 Download
. 279
B.3 Implementation
. 280
B.3.1 Data structures
. 280
B.3.2 Functions
. 280
B.4 How to execute the simulation
. 282
Glossary
283
Author Index
297 |
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| spelling | Fundamentals of grid computing theory, algorithms and technologies ed. by Frédéric Magoulès Boca Raton, Fla. [u.a.] CRC Press 2010 XXI, 298 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier Chapman & Hall/CRC numerical analysis and scientific computing Computational grids (Computer systems) Grid Computing (DE-588)4743648-7 gnd rswk-swf Grid Computing (DE-588)4743648-7 s DE-604 Magoulès, Frédéric Sonstige (DE-588)136913806 oth Digitalisierung UB Bayreuth application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=018808063&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
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| title | Fundamentals of grid computing theory, algorithms and technologies |
| title_auth | Fundamentals of grid computing theory, algorithms and technologies |
| title_exact_search | Fundamentals of grid computing theory, algorithms and technologies |
| title_full | Fundamentals of grid computing theory, algorithms and technologies ed. by Frédéric Magoulès |
| title_fullStr | Fundamentals of grid computing theory, algorithms and technologies ed. by Frédéric Magoulès |
| title_full_unstemmed | Fundamentals of grid computing theory, algorithms and technologies ed. by Frédéric Magoulès |
| title_short | Fundamentals of grid computing |
| title_sort | fundamentals of grid computing theory algorithms and technologies |
| title_sub | theory, algorithms and technologies |
| topic | Computational grids (Computer systems) Grid Computing (DE-588)4743648-7 gnd |
| topic_facet | Computational grids (Computer systems) Grid Computing |
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