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020 _a9783030388362
024 7 _a10.1007/978-3-030-38836-2
_2doi
040 _aES-MaUEC
_bspa
_cES-MaUEC
_dES-MaUEC
050 4 _aQA76.9 .B45
_b2021 EB
245 0 0 _aBig Data Platforms and Applications :
_bCase Studies, Methods, Techniques, and Performance Evaluation
_cedited by Florin Pop, Gabriel Neagu
250 _aFirst edition 2021
264 1 _aCham
_bSpringer International Publising
_c2021
300 _a1 recurso en línea (XVII, 290 páginas)
_b97 ilustraciones, 60 ilustraciones a color
336 _2rdacontent
_aTexto
_btxt
337 _2rdamedia
_aelectrónico
_bc
338 _2rdacarrier
_arecurso electrónico
_bcr
347 _aarchivo de texto
_bPDF
490 0 _aComputer Communications and Networks
_x2197-8433
490 0 _aComputer Science (SpringerNature-11645)
490 0 _aComputer Science (R0) (SpringerNature-43710)
505 0 _a1. 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.
520 3 _aThis 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. Features: * Presents a comprehensive review of the latest developments in big data platforms * Proposes state-of-the-art technological solutions for important issues in big data processing, resource and data management, fault tolerance, and monitoring and controlling * Covers basic theory, new methodologies, innovation trends, experimental results, and implementations of real-world applications 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 needed for 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. Dr. Florin Pop is a professor at the Department of Computer Science and Engineering at the University Politehnica of Bucharest, Romania, and a senior researcher (1st degree) at the Department of Intelligent and Distributed Data Intensive Systems at the National Institute for Research and Development in Informatics, Bucharest, Romania. Dr. Gabriel Neagu is a senior researcher (1st degree) at the Department of Intelligent and Distributed Data Intensive Systems at the National Institute for Research and Development in Informatics, Bucharest, Romania.
988 _aSpringer_Computer_2021
650 7 _2embne
_9495511
_aDatos masivos
700 1 _aPop, Florin
_eeditor literario
700 1 _aNeagu, Gabriel
_eeditor literario
856 4 0 _uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-38836-2
_zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942 _2lcc
_cLE
998 _b02/2022
_dz
_eu
_zSI