Fundamentals of grid computing theory, algorithms and technologies

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Veröffentlicht: Boca Raton, Fla. [u.a.] CRC Press 2010
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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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Boca Raton, Fla. [u.a.] CRC Press 2010
XXI, 298 S. Ill., graph. Darst.
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nc rdacarrier
Chapman & Hall/CRC numerical analysis and scientific computing
Computational grids (Computer systems)
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spellingShingle Fundamentals of grid computing theory, algorithms and technologies
Computational grids (Computer systems)
Grid Computing (DE-588)4743648-7 gnd
subject_GND (DE-588)4743648-7
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
url 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
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