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|a (OCoLC)1142506340
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|a QA76.9.C65
|b S97 2020
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|a 003.3
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|a Systems simulation and modeling for cloud computing and big data applications /
|c edited by J. Dinesh Peter and Steven L. Fernandes.
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|a [Place of publication not identified] :
|b Academic Press,
|c 2020.
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|a 1 online resource
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|a text
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|a Advances in ubiquitous sensing applications for healthcare
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|a Includes index.
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|a Includes bibliographical references and index.
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|a 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.
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|a Computer simulation.
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|a Cloud computing.
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|a Big data.
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|a Digital computer simulation.
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|a Simulation par ordinateur.
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|a simulation.
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|a Digital computer simulation
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|a Computer simulation
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|a Peter, J. Dinesh.
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|a Fernandes, Steven L.
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|a Advances in ubiquitous sensing applications for healthcare.
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|u https://sciencedirect.uam.elogim.com/science/book/9780128197790
|z Texto completo
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