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Intelligent Decision Support Systems for Sustainable Computing

Paradigms and Applications

  • Book
  • © 2017

Overview

Editors:
  1. Arun Kumar Sangaiah

    1. VIT University , Vellore, India

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  2. Ajith Abraham

    1. Sci N/w for Innova and Research Exc, Machine Intelligence Research Labs Sci N/w for Innova and Research Exc, Auburn, USA

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  3. Patrick Siarry

    1. Faculté des Sciences et Technologie, Université Paris-Est Créteil Val-de-Marn Faculté des Sciences et Technologie, Créteil Cedex, France

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  4. Michael Sheng

    1. Faculty of Engig Computer & Math sci, The University of Adelaide Faculty of Engig Computer & Math sci, Adelaide, Australia

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  • Presents the latest research, innovative ideas, challenges, and computational intelligence solutions in sustainable computing
  • Places strong emphasis on real-world applications
  • Includes novel, in-depth fundamental research contributions to achieving a sustainable life style for society either from a methodological or from an application perspective in accomplishing
  • Includes supplementary material: sn.pub/extras

Part of the book series: Studies in Computational Intelligence (SCI, volume 705)

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About this book

This unique book dicusses the latest research, innovative ideas, challenges and computational intelligence (CI) solutions in sustainable computing. It presents novel, in-depth fundamental research on achieving a sustainable lifestyle for society, either from a methodological or from an application perspective.

Sustainable computing has expanded to become a significant research area covering the fields of computer science and engineering, electrical engineering and other engineering disciplines, and there has been an increase in the amount of literature on aspects sustainable computing such as energy efficiency and natural resources conservation that emphasizes the role of ICT (information and communications technology) in achieving system design and operation objectives. The energy impact/design of more efficient IT infrastructures is a key challenge in realizing new computing paradigms.

The book explores the uses of computational intelligence (CI) techniques for intelligent decision support that can be exploited to create effectual computing systems, and addresses sustainability problems in computing and information processing environments and technologies at the different levels of CI paradigms.

An excellent guide to surveying the state of the art in computational intelligence applied to challenging real-world problems in sustainable computing, it is intended for scientists, practitioners, researchers and academicians dealing with the new challenges and advances in area.

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Keywords

Table of contents (14 chapters)

  1. Front Matter

    Pages i-xvi
    Download chapter PDF

  2. Intelligent Decision Support Systems for Sustainable Computing

    • Arun Kumar Sangaiah, Ajith Abraham, Patrick Siarry, Michael Sheng
    Pages 1-6

  3. A Genetic Algorithm Based Efficient Static Load Distribution Strategy for Handling Large-Scale Workloads on Sustainable Computing Systems

    • Xiaoli Wang, Bharadwaj Veeravalli
    Pages 7-31

  4. Efficiency in Energy Decision Support Systems Using Soft Computing Techniques

    • Konstantinos Kokkinos, Elpiniki Papageorgiou, Vassilios Dafopoulos, Ioannis Adritsos
    Pages 33-52

  5. Computational Intelligence Based Heuristic Approach for Maximizing Energy Efficiency in Internet of Things

    • Amandeep Verma, Sakshi Kaushal, Arun Kumar Sangaiah
    Pages 53-76

  6. Distributed Algorithm with Inherent Intelligence for Multi-cloud Resource Provisioning

    • Seyed Ali Miraftabzadeh, Paul Rad, Mo Jamshidi
    Pages 77-99

  7. Parameter Optimization Methods Based on Computational Intelligence Techniques in Context of Sustainable Computing

    • Pankaj Upadhyay, Jitender Kumar Chhabra
    Pages 101-113

  8. The Maximum Power Point Tracking Using Fuzzy Logic Algorithm for DC Motor Based Conveyor System

    • Chitra Venugopal, Prabhakar Rontala Subramaniam
    Pages 115-138

  9. Differential Evolution Based Significant Data Region Identification on Large Storage Drives

    • Nitesh K Bharadwaj, Upasna Singh
    Pages 139-163

  10. A Fuzzy Based Power Switching Selection for Residential Application to Beat Peak Time Power Demand

    • Chitra Venugopal, Prabhakar Rontala Subramaniam, Mathew Habyarimana
    Pages 165-177

  11. Energy Saving Using Memorization: A Novel Energy Efficient and Fault Tolerant Cluster Tree Algorithm for WSN

    • S. S. Jaspal, Umang, Brijesh Kumar
    Pages 179-206

  12. Analyzing Slavic Textual Sentiment Using Deep Convolutional Neural Networks

    • Leo Mršić, Robert Kopal, Goran Klepac
    Pages 207-224

  13. Intelligent Decision Support System for an Integrated Pest Management in Apple Orchard

    • T. Padma, Shabir Ahmad Mir, S. P. Shantharajah
    Pages 225-245

  14. Analysis of Error Propagation in Safety Critical Software Systems: An Approach Based on UGF

    • R. Selvarani, R. Bharathi
    Pages 247-261

  15. A Framework for Analyzing Uncertainty in Data Using Computational Intelligence Techniques

    • M. Sujatha, G. Lavanya Devi, N. Naresh
    Pages 263-285

  16. Back Matter

    Pages 287-289
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Editors and Affiliations

  • VIT University , Vellore, India

    Arun Kumar Sangaiah

  • Sci N/w for Innova and Research Exc, Machine Intelligence Research Labs Sci N/w for Innova and Research Exc, Auburn, USA

    Ajith Abraham

  • Faculté des Sciences et Technologie, Université Paris-Est Créteil Val-de-Marn Faculté des Sciences et Technologie, Créteil Cedex, France

    Patrick Siarry

  • Faculty of Engig Computer & Math sci, The University of Adelaide Faculty of Engig Computer & Math sci, Adelaide, Australia

    Michael Sheng

Bibliographic Information

  • Book Title: Intelligent Decision Support Systems for Sustainable Computing

  • Book Subtitle: Paradigms and Applications

  • Editors: Arun Kumar Sangaiah, Ajith Abraham, Patrick Siarry, Michael Sheng

  • Series Title: Studies in Computational Intelligence

  • DOI: https://doi.org/10.1007/978-3-319-53153-3

  • Publisher: Springer Cham

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer International Publishing AG 2017

  • Hardcover ISBN: 978-3-319-53152-6Published: 23 March 2017

  • Softcover ISBN: 978-3-319-85078-8Published: 21 July 2018

  • eBook ISBN: 978-3-319-53153-3Published: 14 March 2017

  • Series ISSN: 1860-949X

  • Series E-ISSN: 1860-9503

  • Edition Number: 1

  • Number of Pages: XVI, 289

  • Number of Illustrations: 22 b/w illustrations, 86 illustrations in colour

  • Topics: Computational Intelligence, Artificial Intelligence

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