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A Modular and Extensible Network Storage Architecture
Contemporary distributed file systems are monolithic and only support single file abstractions. Nowadays, network storage devices have to be able to accommodate new information …
Hybrid Graph Theory and Network Analysis
First published in 1999, this book combines traditional graph theory with the matroidal view of graphs and throws light on mathematical aspects of network analysis. This approach …
Auction Theory for Computer Networks
Do you have the tools to address recent challenges and problems in modern computer networks? Discover a unified view of auction theoretic applications and develop auction models, …
Security of e-Systems and Computer Networks
E-based systems are ubiquitous in the modern world with applications spanning e-commerce, WLANs, health care and government organisations. The secure transfer of information has …
Processor Networks and Aspects of the Mapping Problem
Here Hilbers discusses the general case of how to use processors simultaneously in order to solve a single problem rather than any specific application, and develops a theory …
Computational Approaches to the Network Science of Teams
Business operations in large organizations today involve massive, interactive, and layered networks of teams and personnel collaborating across hierarchies and countries on complex …
Cellular Neural Networks and Visual Computing
Cellular Nonlinear/neural Network (CNN) technology is both a revolutionary concept and an experimentally proven new computing paradigm. Analogic cellular computers based on CNNs …
Computer Simulation in Brain Science
There has recently been an enormous increase in research activity aimed at elucidating the basis for cortical activity in the brain. Among modern techniques used in this area of …
Deep Learning on Graphs
Deep learning on graphs has become one of the hottest topics in machine learning. The book consists of four parts to best accommodate our readers with diverse backgrounds and …
Data-Driven Computational Neuroscience
Data-driven computational neuroscience facilitates the transformation of data into insights into the structure and functions of the brain. This introduction for researchers and …