Handbook of Data Intensive Computing

Data-intensive computing refers to capturing, managing, analyzing, and understanding data at volumes and rates that push the frontiers of current technologies. This volume of expert commentary addresses matters related to both theory and applications.

Describes and evaluates the current state-of-the-art in new field Presents current systems, and applications from main research labs in this new explosive field Written at a level that business managers, entrepreneurs, and investors will find beneficial Includes supplementary material: sn.pub/extras

Autorentext

Inhalt
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.