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Automated Workflow Scheduling in Self-Adaptive Clouds

Concepts, Algorithms and Methods

  • G. Kousalya
  • P. Balakrishnan
  • C. Pethuru Raj

Part of the Computer Communications and Networks book series (CCN)

Table of contents

  1. Front Matter
    Pages i-xvii
  2. G. Kousalya, P. Balakrishnan, C. Pethuru Raj
    Pages 1-22
  3. G. Kousalya, P. Balakrishnan, C. Pethuru Raj
    Pages 23-53
  4. G. Kousalya, P. Balakrishnan, C. Pethuru Raj
    Pages 55-64
  5. G. Kousalya, P. Balakrishnan, C. Pethuru Raj
    Pages 65-83
  6. G. Kousalya, P. Balakrishnan, C. Pethuru Raj
    Pages 85-101
  7. G. Kousalya, P. Balakrishnan, C. Pethuru Raj
    Pages 103-118
  8. G. Kousalya, P. Balakrishnan, C. Pethuru Raj
    Pages 119-135
  9. G. Kousalya, P. Balakrishnan, C. Pethuru Raj
    Pages 137-156
  10. G. Kousalya, P. Balakrishnan, C. Pethuru Raj
    Pages 157-176
  11. G. Kousalya, P. Balakrishnan, C. Pethuru Raj
    Pages 177-198
  12. G. Kousalya, P. Balakrishnan, C. Pethuru Raj
    Pages 199-221
  13. Back Matter
    Pages 223-225

About this book

Introduction

This timely text/reference presents a comprehensive review of the workflow scheduling algorithms and approaches that are rapidly becoming essential for a range of software applications, due to their ability to efficiently leverage diverse and distributed cloud resources. Particular emphasis is placed on how workflow-based automation in software-defined cloud centers and hybrid IT systems can significantly enhance resource utilization and optimize energy efficiency.

Topics and features:

  • Describes dynamic workflow and task scheduling techniques that work across multiple (on-premise and off-premise) clouds
  • Presents simulation-based case studies, and details of real-time test bed-based implementations
  • Offers analyses and comparisons of a broad selection of static and dynamic workflow algorithms
  • Examines the considerations for the main parameters in projects limited by budget and time constraints
  • Covers workflow management systems, workflow modeling and simulation techniques, and machine learning approaches for predictive workflow analytics

This must-read work provides invaluable practical insights from three subject matter experts in the cloud paradigm, which will empower IT practitioners and industry professionals in their daily assignments. Researchers and students interested in next-generation software-defined cloud environments will also greatly benefit from the material in the book.

Dr. G. Kousalya is a Professor in the Department of Computer Science and Engineering at Coimbatore Institute of Technology, Coimbatore, India. Dr. P. Balakrishnan is an Associate Professor in the Department of Computer Science and Engineering at SASTRA University, Thanjavur, India. Dr. C. Pethuru Raj is the chief architect for Reliance Jio Cloud, Bangalore, India. His other publications include the Springer title High-Performance Big-Data Analytics.

Keywords

Workflow scheduling Cloud computing Workflow modelling and simulation Cloud management optimisation Automated workflow

Authors and affiliations

  • G. Kousalya
    • 1
  • P. Balakrishnan
    • 2
  • C. Pethuru Raj
    • 3
  1. 1.Coimbatore Institute of TechnologyCoimbatoreIndia
  2. 2.SCOPE, VIT UniversityVelloreIndia
  3. 3.Reliance Jio Cloud Services (JCS)BangaloreIndia

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-56982-6
  • Copyright Information Springer International Publishing AG 2017
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-56981-9
  • Online ISBN 978-3-319-56982-6
  • Series Print ISSN 1617-7975
  • Series Online ISSN 2197-8433
  • Buy this book on publisher's site
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