Systems Simulation and Modeling for Cloud Computing and Big Data Applications

Häftad, Engelska, 2020

Del i serien Advances in ubiquitous sensing applications for healthcare

1 188 kr

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Beskrivning

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.

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

Produktinformation

Utgivningsdatum:2020-02-27
Mått:191 x 235 x 15 mm
Vikt:270 g
Format:Häftad
Språk:Engelska
Serie:Advances in ubiquitous sensing applications for healthcare
Antal sidor:182
Förlag:Elsevier Science
ISBN:9780128197790

Utforska kategorier

Nätverk och kommunikation inom Data och IT
Biokemisk teknik inom Naturvetenskap och teknik
Biomedicinsk teknik inom Medicin

Mer om författaren

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. Post-Doctoral Research, Department of Electrical and Computer Engineering , University of Alabama at Birmingham, USAPh.D. in Computer Vision & Machine Learning, Karunya University, Coimbatore, Tamil Nadu, IndiaMaster of Technology, Microelectronics, Manipal Institute of Technology, Manipal, Karnataka, IndiaBachelor of Engineering, Electronics and Communication Engineering,Canara Engineering College, Bantwal, Karnataka, IndiaDecember 2017March 2017June 2011June 2008ACADEMIC 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

Innehållsförteckning

1. Differential Color Harmony: A Robust Approach for Extracting Harmonic Color Features and Perceive Aesthetics in a Large Image Dataset2. Physiological Parameter measurement using wearable sensors and Cloud Computing3. Social Media Data Analytics using Feature Engineering4. A Novel Framework for Quality care in Assisting Chronically Impaired Patients with Ubiquitous Computing and Ambient Intelligence Technologies5. Dynamic and static system modelling with simulations of an eco-friendly smart lighting system6. Predictive analysis of diabetic women patients using R7. IoT Based Smart Mirror for Health Monitoring8. Discovering human influenza virus using ensemble learning9. Mining and Monitoring Human Activity Patterns in Smart Environment Based Health Care Systems10. Early Detection of Cognitive Impairment of Elders using Wearable Sensors11. Analysing plant issues by datasets using four-dimensional-principal component analysis algorithm

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