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Written by Dinesh Peter, this comprehensive book provides readers with the latest approaches to solving problems through the use of models and simulations in cloud computing and big data applications.
In the realm of big data and cloud computing, performance testing and benchmarking are crucial for evaluating the efficiency of different frameworks and applications. Multiple developers and researchers can benefit from controlled and repeatable testing environments, allowing them to analyze the performance of various big data processing and cloud frameworks.
Several benchmarks have been introduced to address the need for performance testing, including BigDataBench, BigBench, HiBench, PigMix, CloudSuite, and GridMix. These benchmarks are all covered in this book, providing readers with a comprehensive understanding of their applications and benefits.
Despite the substantial progress made in benchmarking and performance testing, the research community still requires a holistic and comprehensive big data SSM (Systems Simulation and Modelling) to utilize in various scientific and engineering disciplines. This book aims to develop frameworks that are applicable across disciplines, allowing for the creation of benchmarking tools that can be used in solutions development.
This book examines:
The book also covers the 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.
Product Details:
Publisher: Elsevier Science
Publication Date: February 26, 2020
Language: English
ISBN: 9780128197790 (Hardcover) | 9780128197806 (eBook)
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