Handbook of Data Intensive Computing
Springer-Verlag New York Inc.
978-1-4899-9919-1 (ISBN)
Handbook of Data Intensive Computing is designed as a referencefor practitioners and researchers, including programmers, computer and system infrastructure designers, and developers. This book can also be beneficial for business managers, entrepreneurs, and investors.
PART 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 RankingMethods 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.
Erscheint lt. Verlag | 3.3.2014 |
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Zusatzinfo | XVIII, 794 p. |
Verlagsort | New York |
Sprache | englisch |
Maße | 155 x 235 mm |
Themenwelt | Informatik ► Datenbanken ► Data Warehouse / Data Mining |
Informatik ► Office Programme ► Outlook | |
Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
Mathematik / Informatik ► Mathematik ► Finanz- / Wirtschaftsmathematik | |
Wirtschaft ► Betriebswirtschaft / Management | |
ISBN-10 | 1-4899-9919-1 / 1489999191 |
ISBN-13 | 978-1-4899-9919-1 / 9781489999191 |
Zustand | Neuware |
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