Fundamentals of Grid Computing

Fundamentals of Grid Computing: Theory, Algorithms and Technologies

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Features

  • Focuses on sharing resources, data replication, data management, fault tolerance, scheduling, broadcasting, and load balancing algorithms
  • Discusses emerging and potential developments in grid computing, including grid portals, cloud computing, and service-oriented computing
  • Describes token-based mutual exclusion, selective-rank replication, distributed scheduling, and distributed load balancing algorithms
  • Explores large-scale computing in high energy physics, weather forecasting, genetics, and more
  • Uses simulations to evaluate the performance of models and algorithms
  • Covers two types of easy-to-use open source software written in Java

Summary

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, 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.

Editor Bio(s)

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

Editorial Reviews

… 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

 
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