Optimized Cloud Based Scheduling

  • Rong Kun Jason Tan
  • John A. Leong
  • Amandeep S. Sidhu

Part of the Studies in Computational Intelligence book series (SCI, volume 759)

Also part of the Data, Semantics and Cloud Computing book sub series (DSCC, volume 759)

Table of contents

  1. Front Matter
    Pages i-xiii
  2. Rong Kun Jason Tan, John A. Leong, Amandeep S. Sidhu
    Pages 1-9
  3. Rong Kun Jason Tan, John A. Leong, Amandeep S. Sidhu
    Pages 11-33
  4. Rong Kun Jason Tan, John A. Leong, Amandeep S. Sidhu
    Pages 35-45
  5. Rong Kun Jason Tan, John A. Leong, Amandeep S. Sidhu
    Pages 47-64
  6. Rong Kun Jason Tan, John A. Leong, Amandeep S. Sidhu
    Pages 65-81
  7. Rong Kun Jason Tan, John A. Leong, Amandeep S. Sidhu
    Pages 83-89
  8. Rong Kun Jason Tan, John A. Leong, Amandeep S. Sidhu
    Pages 91-92
  9. Back Matter
    Pages 93-99

About this book

Introduction

This book presents an improved design for service provisioning and allocation models that are validated through running genome sequence assembly tasks in a hybrid cloud environment. It proposes approaches for addressing scheduling and performance issues in big data analytics and showcases new algorithms for hybrid cloud scheduling. Scientific sectors such as bioinformatics, astronomy, high-energy physics, and Earth science are generating a tremendous flow of data, commonly known as big data. In the context of growing demand for big data analytics, cloud computing offers an ideal platform for processing big data tasks due to its flexible scalability and adaptability. However, there are numerous problems associated with the current service provisioning and allocation models, such as inefficient scheduling algorithms, overloaded memory overheads, excessive node delays and improper error handling of tasks, all of which need to be addressed to enhance the performance of big data analytics.

Keywords

Cloud Based Scheduling Cloud Service Provisioning Big Data Big Data Analytics Cloud Computing Hybrid Cloud High Performance Computing

Authors and affiliations

  • Rong Kun Jason Tan
    • 1
  • John A. Leong
    • 2
  • Amandeep S. Sidhu
    • 3
  1. 1.Curtin Sarawak Research InstituteCurtin UniversityMiriMalaysia
  2. 2.Curtin Sarawak Research InstituteCurtin UniversityMiriMalaysia
  3. 3.Biological Mapping Research InstitutePerthAustralia

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-73214-5
  • Copyright Information Springer International Publishing AG 2018
  • Publisher Name Springer, Cham
  • eBook Packages Engineering
  • Print ISBN 978-3-319-73212-1
  • Online ISBN 978-3-319-73214-5
  • Series Print ISSN 1860-949X
  • Series Online ISSN 1860-9503
  • About this book
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