Big Scientific Data Benchmarks Architecture And Systems
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Big Scientific Data Benchmarks, Architecture, and Systems
This book constitutes the refereed proceedings of the First Workshop on Big Scientific Data Benchmarks, Architecture, and Systems, SDBA 2018, held in Beijing, China, in June 2018. The 10 revised full papers presented were carefully reviewed and selected from 22 submissions. The papers are organized in topical sections on benchmarking; performance optimization; algorithms; big science data framework.
Software Architecture for Big Data and the Cloud
Software Architecture for Big Data and the Cloud is designed to be a single resource that brings together research on how software architectures can solve the challenges imposed by building big data software systems. The challenges of big data on the software architecture can relate to scale, security, integrity, performance, concurrency, parallelism, and dependability, amongst others. Big data handling requires rethinking architectural solutions to meet functional and non-functional requirements related to volume, variety and velocity. The book's editors have varied and complementary backgrounds in requirements and architecture, specifically in software architectures for cloud and big data, as well as expertise in software engineering for cloud and big data. This book brings together work across different disciplines in software engineering, including work expanded from conference tracks and workshops led by the editors.
Advancing Big Data Benchmarks
This book constitutes the thoroughly refereed joint proceedings of the Third and Fourth Workshop on Big Data Benchmarking. The third WBDB was held in Xi'an, China, in July 2013 and the Fourth WBDB was held in San José, CA, USA, in October, 2013. The 15 papers presented in this book were carefully reviewed and selected from 33 presentations. They focus on big data benchmarks; applications and scenarios; tools, systems and surveys.