Systems simulation and modeling for cloud computing and big data applications / Dinesh Peter and Steven Fernandes, volume editors.

Contributor(s):

Material type: Text

TextSeries: Advances in ubiquitous sensing applications for healthcare ; 10Publisher: San Diego, California : Academic Press, 2020Description: xv, 165 pages : illustrations ; 24 cmContent type:

text

Media type:

unmediated

Carrier type:

volume

ISBN:

9780128197790

Subject(s):

DDC classification:

003.3 Sy877 23

LOC classification:

QA76.9.C65

Contents:

Differential color harmony: a robust approach for extracting harmonic color features and perceiving aesthetics in a large image dataset -- Physiological parameter measurement using wearable sensors and cloud computing -- Social media data analytics using feature engineering -- A novel framework for quality care assisting chronically impaired patients with ubiquitous computing and ambient intelligence technologies -- Dynamic and static system modeling with simulation of an eco-friendly smart lighting system -- Predictive analysis of diabetic women patients using R -- IoT based smart mirror for health monitoring -- Discovering human influenza virus using ensemble learning -- Mining and monitoring human activity patterns in smart environment-based healthcare systems -- Early detection of cognitive impairment od elders using wearable sensors

Summary: "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"-- Provided by publisher.

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Holdings
Item type	Current library	Shelving location	Call number	Copy number	Status	Date due	Barcode
Books	Main Library-Nabua	Graduate School Library	GRD 003.3 Sy877 2020 (Browse shelf(Opens below))	1-1	Available		026280

Includes bibliographical references and index.

"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"-- Provided by publisher.

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