Fundamentals of Grid Computing: Theory, Algorithms and Technologies

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.

Frédéric Magoulès is a professor in the Applied Mathematics and Systems Laboratory at École Centrale Paris in Châtenay-Malabry, France.

Grid Computing Overview, Frédéric Magoulès, Thi-Mai-Huong Nguyen, and Lei Yu
Introduction
Definitions
Classifying grid systems
Grid applications
Grid architecture
Grid computing projects
Grid evolution
Synchronization Protocols for Sharing Resources in Grid Environments, Julien Sopena, Luciana Arantes, Fabrice Legond-Aubry, and Pierre Sens
Introduction
Token-based mutual exclusion algorithms
Mutual exclusion algorithms for large configurations
Composition approach to mutual exclusion algorithms
Composition properties and its natural effects
Performance evaluation

Data Replication in Grid Environment, Thi-Mai-Huong Nguyen and Frédéric Magoulès
Introduction
Data replication
System architecture
Selective-rank model for replication system
Selective-rank replication algorithm
Evaluation

Data Management in Grids, Jean-Marc Pierson
Introduction
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
Introduction
Several computing paradigm
Definition of cloud computing
Cloud services
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
Introduction
Background and definitions
Multi-objective scheduling for safety
Stable memory-based protocols
Stochastic checkpoint model analysis issues
Implementations

Fault Tolerance for Distributed Scheduling in Grids, Lei Yu and Frédéric Magoulès
Introduction
Fault tolerance in distributed systems
Distributed scheduling model
Fault detection and repairing in the tree structure
Distributed scheduling algorithm
SimGrid and simulation design
Evaluation
Related work
Broadcasting for Grids, Christophe Cérin, Luiz-Angelo Steffenel, and Hazem Fkaier
Introduction
Broadcastings
Heuristics for broadcasting
Related work and related methods

Load Balancing Algorithms for Dynamic Networks, Jacques M. Bahi, Raphaël Couturier, and Abderrahmane Sider
Introduction
A taxonomy for load balancing
Distributed load balancing algorithms for static networks
Distributed load balancing algorithms for dynamic networks
Implementation
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

Index

Concluding remarks and References appear at the end of each chapter.