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.
Table of Contents
Grid Computing Overview. Synchronization Protocols for Sharing Resources in Grid Environments. Data Replication in Grid Environment. Data Management in Grids. Future of Grids Resources Management. Fault Tolerance and Availability Awareness in Computational Grids. Fault Tolerance for Distributed Scheduling in Grids. Broadcasting for Grids. Load Balancing Algorithms for Dynamic Networks. Appendices. Index.
Frédéric Magoulès is a professor in the Applied Mathematics and Systems Laboratory at École Centrale Paris in Châtenay-Malabry, France.