Chapman and Hall/CRC
322 pages | 60 B/W Illus.
The integration and convergence of state-of-the-art technologies in the grid have enabled more flexible, automatic, and complex grid services to fulfill industrial and commercial needs, from the LHC at CERN to meteorological forecasting systems. Fundamentals of Grid Computing: Theory, Algorithms and Technologies discusses how the novel technologies of semantic web and workflow have been integrated into the grid and grid services.
The book explains how distributed mutual exclusion algorithms offer solutions to transmission and control processes. It also addresses the replication problem in data grids with limited replica storage and the problem of data management in grids. After comparing utility, grid, autonomic, and cloud computing, the book presents efficient solutions for the reliable execution of applications in computational grid platforms. It then describes a fault tolerant distributed scheduling algorithm for large-scale distributed applications, along with broadcasting algorithms for institutional grids. The final chapter shows how load balancing is integrated into a real-world scientific application.
Helping readers develop practical skills in grid technology, the appendices introduce user-friendly open source software written in Java. One of the software packages covers strategies for data replication in the grid. The other deals with the implementation of a simulator for distributed scheduling in grid environments.
The various technology presented in this book demonstrates the wide aspects of interest in grid computing as well as the many possibilities and venues that exist in this research area. This interest will only further evolve as numerous exciting developments still await us.
… the common characteristics [of the nine chapters] are the clear exposition and the practical view, especially in what concerns the available implementations of the concepts. … The introductory chapters as well as the ones referring to recent trends can be useful for graduate students who are interested in distributed computing, while the chapters addressing data management, scheduling, synchronization, fault tolerance or broadcasting provide new solutions for researchers and practitioners already initiated in grid computing techniques.
—Zentralblatt MATH, 1191
This book shows, in some sense, the way to the future, where next generation middleware such as those described here will replace in the production infrastructure the more rudimentary ones in use today. Therefore, I am sure that the readers will greatly benefit from this insightful journey in the heart of the grids, a key technology in a very large number of scientific endeavors.
—From the Foreword by Guy Wormser, Institut des Grilles, CNRS, Orsay, France
Grid Computing Overview, Frédéric Magoulès, Thi-Mai-Huong Nguyen, and Lei Yu
Classifying grid systems
Grid computing projects
Synchronization Protocols for Sharing Resources in Grid Environments, Julien Sopena, Luciana Arantes, Fabrice Legond-Aubry, and Pierre Sens
Token-based mutual exclusion algorithms
Mutual exclusion algorithms for large configurations
Composition approach to mutual exclusion algorithms
Composition properties and its natural effects
Data Replication in Grid Environment, Thi-Mai-Huong Nguyen and Frédéric Magoulès
Selective-rank model for replication system
Selective-rank replication algorithm
Data Management in Grids, Jean-Marc Pierson
From data sources to databases … to data sources
Positioning the data management in grids within distributed systems
Links with the other services of the middleware
Problems and some solutions
Toward pervasive, autonomic and on-demand data management
Future of Grids Resources Management, Fei Teng and Frédéric Magoulès
Several computing paradigm
Definition of cloud computing
Cloud resource management
Future direction of resource scheduling
Fault Tolerance and Availability Awareness in Computational Grids, Xavier Besseron, Mohamed-Slim Bouguerra, Thierry Gautier, Erik Saule, and Denis Trystram
Background and definitions
Multi-objective scheduling for safety
Stable memory-based protocols
Stochastic checkpoint model analysis issues
Fault Tolerance for Distributed Scheduling in Grids, Lei Yu and Frédéric Magoulès
Fault tolerance in distributed systems
Distributed scheduling model
Fault detection and repairing in the tree structure
Distributed scheduling algorithm
SimGrid and simulation design
Broadcasting for Grids, Christophe Cérin, Luiz-Angelo Steffenel, and Hazem Fkaier
Heuristics for broadcasting
Related work and related methods
Load Balancing Algorithms for Dynamic Networks, Jacques M. Bahi, Raphaël Couturier, and Abderrahmane Sider
A taxonomy for load balancing
Distributed load balancing algorithms for static networks
Distributed load balancing algorithms for dynamic networks
A practical example: the advection diffusion application
Appendix A: Implementation of the Replication Strategies in OptorSim, Thi-Mai-Huong Nguyen and Frédéric Magoulès
Appendix B: Implementation of the Simulator for the Distributed Scheduling Model, Lei Yu and Frédéric Magoulès
Concluding remarks and References appear at the end of each chapter.