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020 _a9781461414155
_99781461414155
024 7 _a10.1007/9781461414155
_2doi
035 _avtls000340582
039 9 _a201509030349
_bVLOAD
_c201404300417
_dVLOAD
_y201402061029
_zstaff
040 _aMX-SnUAN
_bspa
_cMX-SnUAN
_erda
050 4 _aQA76.9.D3
100 1 _aFurht, Borko.
_eeditor.
_9299355
245 1 0 _aHandbook of Data Intensive Computing /
_cedited by Borko Furht, Armando Escalante.
250 _a1.
264 1 _aNew York, NY :
_bSpringer New York,
_c2011.
300 _axviii, 793 páginas 297 ilustraciones
_brecurso en línea.
336 _atexto
_btxt
_2rdacontent
337 _acomputadora
_bc
_2rdamedia
338 _arecurso en línea
_bcr
_2rdacarrier
347 _aarchivo de texto
_bPDF
_2rda
500 _aSpringer eBooks
505 0 _aPART I ARCHITECTURES AND SYSTEMS -- High Performance Network Architectures for Data Intensive Computing -- Architecting Data-Intensive Software Systems -- ECL: A High-Level Programming Language for Data-Intensive Supercomputing -- Scalable Storage for Data-Intensive Computing -- Computation and Storage Trade-off for Cost-Effective Storage of Scientific Datasets in the Cloud -- PART II TECHNOLOGIES AND TECHNIQUES -- Load Balancing Techniques for Data Intensive Computing -- Resource Management for Data Intensive Clouds Through Dynamic Federation: A Game Theoretic Approach -- SALT: Scalable Automated Linking Technology for Data Intensive Computing -- Parallel Processing, Multiprocessors and Virtualization in Data-Intensive Computing -- Challenges in Data Intensive Analysis and Visualization at Scientific Experimental User Facilities -- Large-Scale Data Analytics Using Ensemble Clustering -- Specification of Data Intensive Applications with Data Dependency and Abstract Clocks -- Ensemble Feature Ranking Methods for Data Intensive Computing Applications -- Record Linkage Methodology and Applications -- Semantic Wrapper: Concise Semantic Querying of Legacy Relational Databases -- PART III SECURITY -- Security in Data Intensive Computing Systems -- Data Security and Privacy in Data-Intensive Supercomputing Clusters -- Information Security in Large Scale Distributed Systems -- Privacy and Security Requirements of Data Intensive Applications in Clouds -- PART IV APPLICATIONS -- On the Processing of Extreme Scale Datasets in the Geosciences -- Parallel Earthquake Simulations on Large-scale Multicore Supercomputers -- Data Intensive Computing in Bioinformatics: A Biomedical Case Study in Gene Selection and Filtering -- Design Space Exploration for Efficient Data Intensive Computing on SoCs -- Discovering Relevant Entities in Large-scale Social Information Systems.-Geospatial Data Management with Terrafly -- An Application for Processing Large and Non-uniform Media Objects on MapReduce-based Clusters -- Feature Selection Algorithms for Mining High-Dimensional DNA Microarray Data -- Application of Random Matrix Theory to Analyze Biological Data -- Keyword Search on Large Relational Databases: an OLAP-Oriented Approach -- A Distributed Publish/Subscribe System for Large Scale Sensor Networks.
520 _aData Intensive Computing refers to capturing, managing, analyzing, and understanding data at volumes and rates that push the frontiers of current technologies. The challenge of data intensive computing is to provide the hardware architectures and related software systems and techniques which are capable of transforming ultra-large data into valuable knowledge. Handbook of Data Intensive Computing is written by leading international experts in the field. Experts from academia, research laboratories and private industry address both theory and application. Data intensive computing demands a fundamentally different set of principles than mainstream computing. Data-intensive applications typically are well suited for large-scale parallelism over the data and also require an extremely high degree of fault-tolerance, reliability, and availability. Real-world examples are provided throughout the book. Handbook of Data Intensive Computing is designed as a reference for practitioners and researchers, including programmers, computer and system infrastructure designers, and developers. This book can also be beneficial for business managers, entrepreneurs, and investors.
590 _aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700 1 _aEscalante, Armando.
_eeditor.
_9313057
710 2 _aSpringerLink (Servicio en línea)
_9299170
776 0 8 _iEdición impresa:
_z9781461414148
856 4 0 _uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-1-4614-1415-5
_zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
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999 _c289018
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