Advances in Grid Computing

This book approaches the grid computing with a perspective on the latest achievements in the field, providing an insight into the current research trends and advances, and presenting a large range of innovative research papers. The topics covered in this book include resource and data management, grid architectures and development, and grid-enabled applications. New ideas employing heuristic methods from swarm intelligence or genetic algorithm and quantum encryption are considered in order to explain two main aspects of grid computing: resource management and data management. The book addresses also some aspects of grid computing that regard architecture and development, and includes a diverse range of applications for grid computing, including possible human grid computing system, simulation of the fusion reaction, ubiquitous healthcare service provisioning and complex water systems

ABSTRACT Topology Information Condensation in Hierarchical Networks.

Inspired by the PNNI protocol of the ATM Forum, this work focuses on the problem of node aggregation within peer groups and link aggregation between peer groups. It is assumed that the (large) network is already divided into peer groups. The objective is to maximally condense topology information subject to a given accuracy constraint. The QoS measures can be reduced into three distinct classes: an additive QoS class, a min-max one and the last, a combination of additive and min-max QoS measures. A new method for node aggregation of the additive QoS class (even with multiple QoS measures) is presented. The min-max class is discussed and Lee’s optimal solution (Lee, 1995) for a single min(max) QoS measure is reviewed. Finally, we discuss the extension of our new method to the combination of additive and min-max QoS measures. A detailed example illustrates the presented algorithm for a single additive QoS measure. Subject to a given relative accuracy ε, it shows how to perform node and link aggregation on different hierarchical levels and how to establish the whole hierarchical structure of the original network