Systems Simulation and Modeling for Cloud Computing and Big Data Applications
- 2h 40m
- J. Dinesh Peter, Steven L. Fernandes (eds)
- Elsevier Science and Technology Books, Inc.
- 2020
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
In this Book
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Differential Color Harmony—A Robust Approach for Extracting Harmonic Color Features and Perceiving Aesthetics in a Large Image Dataset
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Physiological Parameter Measurement Using Wearable Sensors and Cloud Computing
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Social Media Data Analytics Using Feature Engineering
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A Novel Framework for Quality Care in Assisting Chronically Impaired Patients with Ubiquitous Computing and Ambient Intelligence Technologies
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Dynamic and Static System Modeling with Simulation of an Eco-Friendly Smart Lighting System
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Predictive Analysis of Diabetic Women Patients Using R
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IoT-Based Smart Mirror for Health Monitoring
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Discovering Human Influenza Virus Using Ensemble Learning
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Mining and Monitoring Human Activity Patterns in Smart Environment-Based Healthcare Systems
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Early Detection of Cognitive Impairment of Elders Using Wearable Sensors
