Grid Computing: The New Frontier of High Performance Computing
Written by academic and industrial experts who have developed or used grid computing, this text covers most essential and technically relevant issues in grid computing.
TABLE OF CONTENTS Grid Computing: The New Frontier of High Performance Computing
Operations Research Methods for Resource Management and Scheduling in a Computational Grid: a Survey
Andrea Attanasio [a], Gianpaolo Ghiani [b], Lucio Grandinetti [a], Emanuela Guerriero [b], Francesca Guerriero [a]
Overview
Computational grids are emerging as the new generation computing paradigm for tackling large scale hard problems in a wide range of scientific fields. Grids are highly complex distributed systems (involving multiple organizations with different goals and policies) which aim at providing computing services without the users need to know the location and features of the required resources. While the current and previous research efforts have been mainly concentrated on architectures and protocols, this paper deals with quantitative methods for grid resource management. In particular, three main issues are considered: performance forecasting, local scheduling (i.e., job scheduling within a single administrative domain) and distributed mechanisms for coordinating grid resources within several administrative domains. For each such a topic, the current literature is reviewed and new research avenues are highlighted.
[a]Center of Excellence on High-Performance Computing and Dipartimento di Elettronica, Informatica e Sistemistica, Universita degli Studi della Calabria, Via P. Bucci 41C, Rende (CS) 87030, Italy
[b]Dipartimento di Ingegneria dell'Innovazione, Universita degli Studi di Lecce, Via Arnesano, Lecce 73100, Italy
1. Introduction
A "computational grid" is a collection of geographically distributed, loosely coupled, heterogeneous, non-dedicated computing resources, belonging to several organizations, which provide computing services without users know the location and features of the involved resources [1] (Figure 1). The resources shared and aggregated in order to provide the required services may include: processors; nodes with arithmetic, vector, graphic, signal...
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