Systems Simulation and Modeling for Cloud Computing and Big Data Applications

Systems Simulation and Modeling for Cloud Computing and Big Data Applications

1st Edition - February 26, 2020

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  • Editors: Dinesh Peter, Steven Fernandes
  • Paperback ISBN: 9780128197790
  • eBook ISBN: 9780128197806

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Systems Simulation and Modelling for Cloud Computing and Big Data Applications provides readers with the most current approaches to solving problems through the use of models and simulations, presenting SSM based approaches to performance testing and benchmarking that offer significant advantages. For example, multiple big data and cloud application developers and researchers can perform tests in a controllable and repeatable manner. Inspired by the need to analyze the performance of different big data processing and cloud frameworks, researchers have introduced several benchmarks, including BigDataBench, BigBench, HiBench, PigMix, CloudSuite and GridMix, which are all covered in this book. Despite the substantial progress, the research community still needs a holistic, comprehensive big data SSM to use in almost every scientific and engineering discipline involving multidisciplinary research. SSM develops frameworks that are applicable across disciplines to develop benchmarking tools that are useful in solutions development.

Key Features

  • Examines the methodology and requirements of benchmarking big data and cloud computing tools, advances in big data frameworks and benchmarks for large-scale data analytics, and frameworks for benchmarking and predictive analytics in big data deployment
  • Discusses applications using big data benchmarks, such as BigDataBench, BigBench, HiBench, MapReduce, HPCC, ECL, HOBBIT, GridMix and PigMix, and applications using big data frameworks, such as Hadoop, Spark, Samza, Flink and SQL frameworks
  • Covers development of big data benchmarks to evaluate workloads in state-of-the-practice heterogeneous hardware platforms, advances in modeling and simulation tools for performance evaluation, security problems and scalable cloud computing environments


Systems designers, biomedical engineers, biomedical researchers and policy makers in health care and medicine

Table of Contents

  • 1. Differential Color Harmony: A Robust Approach for Extracting Harmonic Color Features and Perceive Aesthetics in a Large Image Dataset
    Tousif Osman, Shahreen Shahjahan Psyche, Tonmoay Deb, Adnan Firoze and Rashedur M. Rahman
    2. Physiological Parameter measurement using wearable sensors and Cloud Computing
    Anitha Mary, Shobha Mohan, Suganthi Evangeline and K. Rajasekaran
    3. Social Media Data Analytics using Feature Engineering
    J Anitha, I-Hsien Ting, Akila Agnes S, S. Immanuel Alex Pandian and Belfin R V
    4. A Novel Framework for Quality care in Assisting Chronically Impaired Patients with Ubiquitous Computing and Ambient Intelligence Technologies
    Deva Priya Isravel, Diana Arulkumar, Kumudha Raimond and Biju Issac
    5. Dynamic and static system modelling with simulations of an eco-friendly smart lighting system
    Titus Issac, Salaja Silas and Elijah Blessing Rajsingh
    6. Predictive analysis of diabetic women patients using R
    R.Rifat Ameena and B. Ashadevi
    7. IoT Based Smart Mirror for Health Monitoring
    Ilango Krishnamurthy, Prabha D and Karthika M S
    8. Discovering human influenza virus using ensemble learning
    Nandhini M and Vijaya MS
    9. Mining and Monitoring Human Activity Patterns in Smart Environment Based Health Care Systems
    Nataraj Muthusamy, Shyam Ganesh Ramprakash and Janani Muthusamy Jr.
    10. Early Detection of Cognitive Impairment of Elders using Wearable Sensors
    S. Meenakshi Ammal and L. S. Jayashree
    11. Analysing plant issues by datasets using four-dimensional-principal component analysis algorithm
    Kalaiselvi Duraisamy, Kalaiabirami Duraisamy, R Rajkumar, E R. Ahilan, keerthana balamurugan and M Kanimozhi

Product details

  • No. of pages: 182
  • Language: English
  • Copyright: © Academic Press 2020
  • Published: February 26, 2020
  • Imprint: Academic Press
  • Paperback ISBN: 9780128197790
  • eBook ISBN: 9780128197806

About the Editors

Dinesh Peter

J. Dinesh Peter is Program Coordinator for the Department of Computer Sciences Technology at Karunya University, and author of more than 25 academic articles/chapters/conference papers. He has been active in government and industry as the developer of new technologies including Digital Image Processing, Virtual Reality Technology, Medical Image Processing, Computer Vision, and Optimization. He has been Guest Editor of a special issue of the Elsevier journal Computers and Electrical Engineering, and Guest Editor of special issues of the Journal of Cloud Computing and Journal of Big Data Intelligence. Dr. Peter received his Ph.D. in Computer Science and Engineering from National Institute of Technology Calicut, India.

Affiliations and Expertise

Associate Professor, Department of Computer Sciences Technology, Karunya University, India

Steven Fernandes

Post-Doctoral Research, Department of Electrical and Computer Engineering , University of Alabama at Birmingham, USA Ph.D. in Computer Vision & Machine Learning, Karunya University, Coimbatore, Tamil Nadu, India Master of Technology, Microelectronics, Manipal Institute of Technology, Manipal, Karnataka, India Bachelor of Engineering, Electronics and Communication Engineering, Canara Engineering College, Bantwal, Karnataka, India December 2017 March 2017 June 2011 June 2008 ACADEMIC AND TECHNICAL WORK EXPERIENCE ● Assistant Professor, Department of Electronics and Communication Engineering, Sahyadri College of Engineering and Management, India, June 2014 – June 2017 ● Senior Software Test Analysts, Perform Group Pvt. Ltd., India April 2011 – June 2014

Affiliations and Expertise

Post-Doctoral Researcher, Department of Electrical and Computer Engineering, University of Alabama at Birmingham, USA

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