Communication Systems

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Srihari Nelakuditi, Zhi-Li Zhang

Under Quality of Service (QoS) routing, paths for flows are selected based upon the knowledge of resource availability at network nodes and the QoS requirements of flows. QoS routing schemes proposed differ in the way they gather information about the network state and select paths based on this information. We broadly categorize these schemes into best-path routing and proportional routing. The best-path routing schemes gather global network state information and always select the best path for an incoming flow based on this global view. On the other hand, proportional routing schemes proportion incoming flows among a set of candidate paths. We have shown that it is possible to compute near-optimal proportions using only locally collected information. Furthermore, a few good candidate paths can be selected using infrequently exchanged global information and thus with minimal communication overhead. Localized Quality Of Service Routing For The Internet, describes these schemes in detail demonstrating that proportional routing schemes can achieve higher throughput with lower overhead than best-path routing schemes. It first addresses the issue of finding near-optimal proportions for a given set of candidate paths based on locally collected flow statistics. This book will also look into the selection of a few good candidate paths based on infrequently exchanged global information. The final phase of this book will describe extensions to proportional routing approach to provide hierarchical routing across multiple areas in a large network. Localized Quality Of Service Routing For The Internet is designed for researchers and practitioners in industry, and is suitable for graduate level students in computer science as a secondary text.

Sample

Alan F. Murray

Applications of Neural Networks gives a detailed description of 13 practical applications of neural networks, selected because the tasks performed by the neural networks are real and significant. The contributions are from leading researchers in neural networks and, as a whole, provide a balanced coverage across a range of application areas and algorithms. The book is divided into three sections. Section A is an introduction to neural networks for nonspecialists. Section B looks at examples of applications using `Supervised Training'. Section C presents a number of examples of `Unsupervised Training'. For neural network enthusiasts and interested, open-minded sceptics. The book leads the latter through the fundamentals into a convincing and varied series of neural success stories -- described carefully and honestly without over-claiming. Applications of Neural Networks is essential reading for all researchers and designers who are tasked with using neural networks in real life applications.

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Robert J. Jannarone

Many monitoring, forecasting, and control operations occur in settings where relationships among key measurements must be learned quickly. Examples are on-line industrial processes where influent material is not consistent over time, energy load or price forecasting where demand characteristics change rapidly,and health management where relationships among monitored variables must be learned for each patient-treatment combination. The solution presented is a new neuro-computing system that learns in real-time, even when data arrival rates are several million measurements per second. The book describes benefits and features of the system, statistical foundations for the system, and several related models. The book also describes available system software.

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Jean-Claude Geffroy, Gilles Motet

Today computing systems are more and more complex and they assume more and more responsibilities in all sectors of human activity. Unfortunately, many faults can harm the development or the use of these products. Destructive mechanisms transform faults into errors and finally failures altering the delivered service. For critical systems, the consequences of these failures can be catastrophic, but for most non-critical systems, failures are nowadays unacceptable. Hence, it is necessary to take dependability attributes into account, along the product lifecycle. This book aims at providing a general overview of the dependability of computing systems: impairments and protective means. Issues, concepts and techniques are considered from a system point of view, and are illustrated by both hardware and software technologies. An important pedagogical effort has been made: the explanations are illustrated by 370 figures, 80 examples, and 97 exercises with complete answers. A glossary of more than 500 entries defines the important terms.