Large Scale Networks
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| Author | : Peter Benner |
| Publisher | : Springer |
| Total Pages | : 401 |
| Release | : 2014-10-21 |
| Genre | : Mathematics |
| ISBN | : 3319084372 |
This edited volume provides insights into and tools for the modeling, analysis, optimization, and control of large-scale networks in the life sciences and in engineering. Large-scale systems are often the result of networked interactions between a large number of subsystems, and their analysis and control are becoming increasingly important. The chapters of this book present the basic concepts and theoretical foundations of network theory and discuss its applications in different scientific areas such as biochemical reactions, chemical production processes, systems biology, electrical circuits, and mobile agents. The aim is to identify common concepts, to understand the underlying mathematical ideas, and to inspire discussions across the borders of the various disciplines. The book originates from the interdisciplinary summer school “Large Scale Networks in Engineering and Life Sciences” hosted by the International Max Planck Research School Magdeburg, September 26-30, 2011, and will therefore be of interest to mathematicians, engineers, physicists, biologists, chemists, and anyone involved in the network sciences. In particular, due to their introductory nature the chapters can serve individually or as a whole as the basis of graduate courses and seminars, future summer schools, or as reference material for practitioners in the network sciences.
| Author | : Alessandro Vespignani |
| Publisher | : World Scientific |
| Total Pages | : 264 |
| Release | : 2007-06-28 |
| Genre | : Computers |
| ISBN | : 9814475416 |
This book is the culmination of three years of research effort on a multidisciplinary project in which physicists, mathematicians, computer scientists and social scientists worked together to arrive at a unifying picture of complex networks. The contributed chapters form a reference for the various problems in data analysis visualization and modeling of complex networks.
| Author | : Alex Fornito |
| Publisher | : Academic Press |
| Total Pages | : 496 |
| Release | : 2016-03-04 |
| Genre | : Medical |
| ISBN | : 0124081185 |
Fundamentals of Brain Network Analysis is a comprehensive and accessible introduction to methods for unraveling the extraordinary complexity of neuronal connectivity. From the perspective of graph theory and network science, this book introduces, motivates and explains techniques for modeling brain networks as graphs of nodes connected by edges, and covers a diverse array of measures for quantifying their topological and spatial organization. It builds intuition for key concepts and methods by illustrating how they can be practically applied in diverse areas of neuroscience, ranging from the analysis of synaptic networks in the nematode worm to the characterization of large-scale human brain networks constructed with magnetic resonance imaging. This text is ideally suited to neuroscientists wanting to develop expertise in the rapidly developing field of neural connectomics, and to physical and computational scientists wanting to understand how these quantitative methods can be used to understand brain organization. - Winner of the 2017 PROSE Award in Biomedicine & Neuroscience and the 2017 British Medical Association (BMA) Award in Neurology - Extensively illustrated throughout by graphical representations of key mathematical concepts and their practical applications to analyses of nervous systems - Comprehensively covers graph theoretical analyses of structural and functional brain networks, from microscopic to macroscopic scales, using examples based on a wide variety of experimental methods in neuroscience - Designed to inform and empower scientists at all levels of experience, and from any specialist background, wanting to use modern methods of network science to understand the organization of the brain
| Author | : Radu Dobrescu |
| Publisher | : CRC Press |
| Total Pages | : 217 |
| Release | : 2016-10-03 |
| Genre | : Computers |
| ISBN | : 1315351390 |
This book offers a rigorous analysis of the achievements in the field of traffic control in large networks, oriented on two main aspects: the self-similarity in traffic behaviour and the scale-free characteristic of a complex network. Additionally, the authors propose a new insight in understanding the inner nature of things, and the cause-and-effect based on the identification of relationships and behaviours within a model, which is based on the study of the influence of the topological characteristics of a network upon the traffic behaviour. The effects of this influence are then discussed in order to find new solutions for traffic monitoring and diagnosis and also for traffic anomalies prediction. Although these concepts are illustrated using highly accurate, highly aggregated packet traces collected on backbone Internet links, the results of the analysis can be applied for any complex network whose traffic processes exhibit asymptotic self-similarity, perceived as an adaptability of traffic in networks. However, the problem with self-similar models is that they are computationally complex. Their fitting procedure is very time-consuming, while their parameters cannot be estimated based on the on-line measurements. In this aim, the main objective of this book is to discuss the problem of traffic prediction in the presence of self-similarity and particularly to offer a possibility to forecast future traffic variations and to predict network performance as precisely as possible, based on the measured traffic history.
| Author | : Antonio Nucci |
| Publisher | : Cambridge University Press |
| Total Pages | : 407 |
| Release | : 2009 |
| Genre | : Computers |
| ISBN | : 0521880696 |
Sets out the design and management principles of large-scale IP networks by weaving together theory and practice.
| Author | : Olaf Sporns |
| Publisher | : MIT Press |
| Total Pages | : 433 |
| Release | : 2016-02-12 |
| Genre | : Medical |
| ISBN | : 0262528983 |
An integrative overview of network approaches to neuroscience explores the origins of brain complexity and the link between brain structure and function. Over the last decade, the study of complex networks has expanded across diverse scientific fields. Increasingly, science is concerned with the structure, behavior, and evolution of complex systems ranging from cells to ecosystems. In Networks of the Brain, Olaf Sporns describes how the integrative nature of brain function can be illuminated from a complex network perspective. Highlighting the many emerging points of contact between neuroscience and network science, the book serves to introduce network theory to neuroscientists and neuroscience to those working on theoretical network models. Sporns emphasizes how networks connect levels of organization in the brain and how they link structure to function, offering an informal and nonmathematical treatment of the subject. Networks of the Brain provides a synthesis of the sciences of complex networks and the brain that will be an essential foundation for future research.
| Author | : |
| Publisher | : |
| Total Pages | : 64 |
| Release | : 2001 |
| Genre | : Computer networks |
| ISBN | : |
| Author | : Daniel Hitchcock |
| Publisher | : DIANE Publishing |
| Total Pages | : 58 |
| Release | : 2009-03-01 |
| Genre | : |
| ISBN | : 143791022X |
Documents the findings of a workshop held in 2001 to develop a vision for the future of networking (10-20 years out) and to identify needed Fed. networking research to enable that vision. The Workshop was attended by more than 160 leading networking researchers from universities, industry, gov¿t., and laboratories. The participants concluded that industry is not prepared to do the long-term research needed to enable the workshop visions for future networking. Industry is oriented toward near-term development and is currently scaling back the corporate ability to provide networking research. This places increased responsibility on Fed. agencies to fund and conduct the research needed to support the continuing growth of the Internet.
| Author | : Valery A. Kalyagin |
| Publisher | : Springer |
| Total Pages | : 358 |
| Release | : 2018-08-24 |
| Genre | : Business & Economics |
| ISBN | : 3319962477 |
Contributions in this volume focus on computationally efficient algorithms and rigorous mathematical theories for analyzing large-scale networks. Researchers and students in mathematics, economics, statistics, computer science and engineering will find this collection a valuable resource filled with the latest research in network analysis. Computational aspects and applications of large-scale networks in market models, neural networks, social networks, power transmission grids, maximum clique problem, telecommunication networks, and complexity graphs are included with new tools for efficient network analysis of large-scale networks. This proceeding is a result of the 7th International Conference in Network Analysis, held at the Higher School of Economics, Nizhny Novgorod in June 2017. The conference brought together scientists, engineers, and researchers from academia, industry, and government.
| Author | : Kanthavel, R. |
| Publisher | : IGI Global |
| Total Pages | : 534 |
| Release | : 2024-10-25 |
| Genre | : Computers |
| ISBN | : |
Artificial Intelligence (AI) is rapidly becoming essential to large-scale communication networks. Driven by the need for greater efficiency, security, and optimization, AI has evolved into a powerful tool that processes vast data and delivers insights through real-time processing, predictive analysis, and adaptive learning. Because these advancements transform how we interact with data and services, applying AI to complex networks has never been more essential. AI for Large Scale Communication Networks explores how AI can enhance network performance, scalability, and security. With contributions from experts, this book covers topics such as algorithm optimization, machine learning improvements, and neural network applications. It also addresses critical challenges like fault tolerance and distributed computing, emphasizing the need for interdisciplinary collaboration. Designed for academics, practitioners, and students, this resource provides actionable insights and strategies to optimize communication networks using AI.
