Systems Simulation and Modeling for Cloud Computing and Big Data Applications - Info and Reading Options
By Dinesh Peter and Steven L. Fernandes
"Systems Simulation and Modeling for Cloud Computing and Big Data Applications" was published by Elsevier Science & Technology Books in 2020 - S.l., it has 182 pages and the language of the book is English.
“Systems Simulation and Modeling for Cloud Computing and Big Data Applications” Metadata:
- Title: ➤ Systems Simulation and Modeling for Cloud Computing and Big Data Applications
- Authors: Dinesh PeterSteven L. Fernandes
- Language: English
- Number of Pages: 182
- Publisher: ➤ Elsevier Science & Technology Books
- Publish Date: 2020
- Publish Location: S.l.
“Systems Simulation and Modeling for Cloud Computing and Big Data Applications” Subjects and Themes:
- Subjects: Biomedical engineering - Biotechnology
Edition Identifiers:
- The Open Library ID: OL28055872M - OL20742773W
- ISBN-13: 9780128197806
- All ISBNs: 9780128197806
AI-generated Review of “Systems Simulation and Modeling for Cloud Computing and Big Data Applications”:
"Systems Simulation and Modeling for Cloud Computing and Big Data Applications" Description:
Open Data:
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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