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© 2012

Evolutionary Hierarchical Multi-Criteria Metaheuristics for Scheduling in Large-Scale Grid Systems

  • Complete coverage of the latest research on the novel bio-inspired hierarchic scalable models and methodologies in dynamic grid scheduling

  • Presents a detailed classification of scheduling problems

  • Proposes a new metaheuristic framework which can be easily adapted to various scheduling scenarios as well as for the design of well known bio-inspired grid schedulers

Book

Part of the Studies in Computational Intelligence book series (SCI, volume 419)

Table of contents

  1. Front Matter
    Pages 1-23
  2. Scheduling Problems in Grid Computing

    1. Front Matter
      Pages 1-1
  3. Multi-Level Genetic-Based Hierarchical Grid Schedulers

  4. Security-Driven Scheduling Model for Computational Grid Using Multi-Level Genetic Metaheuristics

  5. Genetic Solutions to Green Scheduling in Computational Grids

  6. Back Matter
    Pages 0--1

About this book

Introduction

One of the most challenging issues in modelling today's large-scale computational systems is to effectively manage highly parametrised distributed environments such as computational grids, clouds, ad hoc networks and P2P networks. Next-generation computational grids must

provide a wide range of services and high performance computing infrastructures. Various types of information and data processed in the large-scale dynamic grid environment may be incomplete, imprecise, and fragmented, which complicates the specification of proper evaluation criteria and which affects both the availability of resources and the final collective decisions of users. The complexity of grid architectures and grid management may also contribute towards higher energy consumption. All of these issues necessitate the development of intelligent resource management techniques, which are capable of capturing all of this complexity and optimising meaningful metrics for a wide range of grid applications.

 

This book covers hot topics in the design, administration and management of dynamic grid environments with a special emphasis on the preferences and autonomous decisions of system users, secure access to the processed data and services, and application of green technologies. It features advanced research related to scalable genetic-based heuristic approaches to grid scheduling, whereby new scheduling criteria, such as system reliability, security, and energy consumption are incorporated into a general scheduling model. This book may be a valuable reference for students, researchers, and practitioners who work on – or who are interested in joining -- interdisciplinary research efforts in the areas of distributed and evolutionary computation.

 

Keywords

Artificial Intelligence Computational Intelligence Genetic Algorithms Green Computing Grid Computing Meta-Heuristics Scalable Computing

Authors and affiliations

  1. 1.Cracow University of TechnologyCracowPoland

Bibliographic information

  • Book Title Evolutionary Hierarchical Multi-Criteria Metaheuristics for Scheduling in Large-Scale Grid Systems
  • Authors Joanna Kołodziej
  • Series Title Studies in Computational Intelligence
  • DOI https://doi.org/10.1007/978-3-642-28971-2
  • Copyright Information Springer-Verlag Berlin Heidelberg 2012
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering Engineering (R0)
  • Hardcover ISBN 978-3-642-28970-5
  • Softcover ISBN 978-3-642-43661-1
  • eBook ISBN 978-3-642-28971-2
  • Series ISSN 1860-949X
  • Series E-ISSN 1860-9503
  • Edition Number 1
  • Number of Pages XXVIII, 191
  • Number of Illustrations 44 b/w illustrations, 0 illustrations in colour
  • Topics Computational Intelligence
    Artificial Intelligence
  • Buy this book on publisher's site
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