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检索条件"主题词=Big data reference architecture"

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NIST big data reference architecture for Analytics and Beyond 17

NIST Big Data Reference Architecture for Analytics and Beyon...

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10th International Conference on Utility and Cloud Computing (UCC) / 4th International Conference on big data Computing, Applications and Technologies (BDCAT)

作者： Chang, Wo NIST Informat Technol Lab ITL Gaithersburg MD 20899 USA

ISBN: (纸本)9781450351492

big data is the term used to describe the deluge of data in our networked, digitized, sensor-laden, information driven world. There is a broad agreement among commercial, academic, and government leaders about the remarkable potential of "big data" to spark innovation, fuel commerce, and drive progress. The availability of vast data resources carries the potential to answer questions previously out of reach. However, there is also broad agreement on the ability of big data to overwhelm traditional approaches. big data architectures come in many shapes and forms ranging from academic research settings to product-oriented workflows. With massive-scale dynamic data being generate from social media, Internet of Things, Smart Cities, and others, it is critical to analyze these data in real-time and provide proactive decision. With the advancement of computer architecture in multi-cores and GPUs, and fast communication between CPUs and GPUs, parallel processing utilizes these platforms could optimize resources at a reduced time. This presentation will provide the past, current, and future activities of the NIST big data Public Working Group (NBD-PWG) and how the NIST reference architecture may address the rate at which data volumes, speeds, and complexity are growing requires new forms of computing infrastructure to enable big data analytics interoperability such that analytics tools can be re-usable, deployable, and operational. The focus of NBD-PWG is to form a community of interest from industry, academia, and government, with the goal of developing consensus definitions, taxonomies, secure reference architectures, and standards roadmap which would create vendor-neutral, technology and infrastructure agnostic framework. The aim is to enable big data stakeholders to pick-and-choose best analytics tools for their processing under the most suitable computing platforms and clusters while allowing value-additions from big data service providers and flow of data between the

关键词： big data reference architecture big data Analytics high-performance computing Many CPUs/Cores/GPUs

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Towards a domain-driven distributed reference architecture for big data systems 29

Towards a domain-driven distributed reference architecture f...

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29th Annual Americas Conference on Information Systems: Diving into Uncharted Waters, AMCIS 2023

作者： Ataei, Pouya Litchfield, Alan School of Engineering Computer and Mathematical Sciences New Zealand Service and Cloud Computing Research Lab New Zealand

ISBN: (纸本)9781713893592

The proliferation of digital devices, rapid development of software and the infrastructure of today, have augmented user’s capability to produce data at an unprecedented rate. The accelerated growth of data could be called the era of big data and forced a paradigm shift in data engineering because the variety, velocity and volume of data overwhelmed existing systems. While companies attempt to extract benefit from big data, success rates are still low. Challenges such as rapid changes in technology, organizational culture, complexity in data engineering, impediments to system development, and a lack of effective big data architectures mean that only an estimated 20% of companies achieved their goals. To this end, this study explores a domain-driven distributed big data reference architecture that addresses issues in data architecture, data engineering, and system development. This reference architecture is empirically grounded and evaluated through deployment in a real-world scenario as an instantiated prototype, solving a problem in practice. The results of the evaluation demonstrate utility and applicability but with architectural trade-offs and challenges. © 2023 29th Annual Americas Conference on Information Systems, AMCIS 2023. All rights reserved.

关键词： big data big data architecture big data reference architecture data architecture data engineering

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NeoMycelia: A software reference architecturefor big data systems 28

NeoMycelia: A software reference architecturefor big data sy...

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28th Asia-Pacific Software Engineering Conference (APSEC)

作者： Ataei, Pouya Litchfield, Alan Auckland Univ Technol Sch Engn Comp & Math Sci Auckland New Zealand Auckland Univ Technol Serv & Cloud Comp Res Lab Auckland New Zealand

ISBN: (纸本)9781665437844

The big data revolution began when the volume, velocity, and variety of data completely overwhelmed the systems used to store, manipulate and analyze that data. As a result, a new class of software systems emerged called big data systems. While many attempted to harness the power of these new systems, it is estimated that approximately 75% of the big data projects have failed within the last decade. One of the root causes of this is software engineering and architecture aspect of these systems. This paper aims to facilitate big data system development by introducing a software reference architecture. The work provides an event driven microservices architecture that addresses specific limitations in current big data reference architectures (RA). The artefact development has followed the principles of empirically grounded RAs. The RA has been evaluated by developing a prototype that solves a real-world problem in practice. At the end, succesful implementation of the reference architecture have been presented. The results displayed a good degree of applicability with respect to quality factors.

关键词： reference architecture architecture big data reference architecture big data architecture big data systems big data software engineering Event driven Microservices

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