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5 - Grid networking

from Part I - Enabling technologies

Published online by Cambridge University Press:  05 October 2012

Anusha Ravula
Affiliation:
University of Nebraska-Lincoln, USA
Byrav Ramamurthy
Affiliation:
University of Nebraska-Lincoln, USA
Byrav Ramamurthy
Affiliation:
University of Nebraska, Lincoln
George N. Rouskas
Affiliation:
North Carolina State University
Krishna Moorthy Sivalingam
Affiliation:
Indian Institute of Technology, Madras
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Summary

Research in Grid Computing has become popular with the growth in network technologies and high-performance computing. Grid Computing demands the transfer of large amounts of data in a timely manner.

In this chapter, we discuss Grid Computing and networking. We begin with an introduction to Grid Computing and discuss its architecture. We provide some information on Grid networks and continue with various current applications of Grid networking. The remainder of the chapter is devoted to research in Grid networks. We discuss the techniques developed by various researchers with respect to resource scheduling in Grid networks.

Introduction

Today, the demand for computational, storage, and network resources continues to grow. At the same time, a vast amount of these resources remains underused. To enable the increased utilization of these resources the tasks can be executed using shared computational and storage resources while communicating over a network. Imagine a team of researchers performing a job which contains a number of tasks. Each task demands different computational, storage, and network resources. Distributing the tasks across a network according to resource availability is called distributed computing. Grid Computing is a recent phenomenon in distributed computing. The term “The Grid” was coined in the mid 1990s to denote a proposed distributed computing infrastructure for advanced science and engineering.

Grid Computing enables efficient utilization of geographically distributed and heterogeneous computational resources to execute large-scale scientific computing applications.

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