Big Data Platforms and Applications : Case Studies, Methods, Techniques, and Performance Evaluation (Computer Communications and Networks) / Pop, Florin (EDT)/ Neagu, Gabriel (EDT)

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Big Data Platforms and Applications : Case Studies, Methods, Techniques, and Performance Evaluation (Computer Communications and Networks)

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Big Data Platforms and Applications : Case Studies, Methods, Techniques, and Performance Evaluation (Computer Communications and Networks)

Pop, Florin (EDT)/ Neagu, Gabriel (EDT)

ウェブストア価格 ¥40,829（本体¥37,118）
Springer Nature Switzerland AG（2022/09発売）
外貨定価 US$ 199.99
ポイント 371pt

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製本 Paperback:紙装版/ペーパーバック版／ページ数 290 p.
商品コード 9783030388386

Full Description

This book provides a review of advanced topics relating to the theory, research, analysis and implementation in the context of big data platforms and their applications, with a focus on methods, techniques, and performance evaluation.

The explosive growth in the volume, speed, and variety of data being produced every day requires a continuous increase in the processing speeds of servers and of entire network infrastructures, as well as new resource management models. This poses significant challenges (and provides striking development opportunities) for data intensive and high-performance computing, i.e., how to efficiently turn extremely large datasets into valuable information and meaningful knowledge.

The task of context data management is further complicated by the variety of sources such data derives from, resulting in different data formats, with varying storage, transformation, delivery, and archiving requirements. At the same time rapid responses are neededfor real-time applications. With the emergence of cloud infrastructures, achieving highly scalable data management in such contexts is a critical problem, as the overall application performance is highly dependent on the properties of the data management service.

1. Data Center for Smart Issues: Energy and Sustainability Issue.- 2 Apache Spark for Digitalization, Analysis and Optimization of Discrete Manufacturing Process.- 3. An Empirica Study on Teleworking among Slovakia's Office-Based Academics.- 4. DSS for Pro-Active Flood Management of Water Reservoir Systems.- 5. exhiSTORY: Small Self-Organizing Exhibits.- 6. IoT Cloud Design Patterns.- 7. Cloud-based mHealth Streaming for IoT Processing.- 8. A System for Monitoring Water Quality Parameters in Rivers: Challenges and Solutions.