Establishing adaptive control as an alternative framework to design and analyze Internet congestion controllers, End-to-End Adaptive Congestion Control in TCP/IP Networks employs a rigorously mathematical approach coupled with a lucid writing style to provide extensive background and introductory material on dynamic systems stability and neural network approximation; alongside future internet requests for congestion control architectures. Designed to operate under extreme heterogeneous, dynamic, and time-varying network conditions, the developed controllers must also handle network modeling structural uncertainties and uncontrolled traffic flows acting as external perturbations. The book also presents a parallel examination of specific adaptive congestion control, NNRC, using adaptive control and approximation theory, as well as extensions toward cooperation of NNRC with application QoS control.
Features:
Uses adaptive control techniques for congestion control in packet switching networks
Employs a rigorously mathematical approach with lucid writing style
Presents simulation experiments illustrating significant operational aspects of the method; including scalability, dynamic behavior, wireless networks, and fairness
Applies to networked applications in the music industry, computers, image trading, and virtual groups by techniques such as peer-to-peer, file sharing, and internet telephony
Contains working examples to highlight and clarify key attributes of the congestion control algorithms presented
Drawing on the recent research efforts of the authors, the book offers numerous tables and figures to increase clarity and summarize the algorithms that implement various NNRC building blocks. Extensive simulations and comparison tests analyze its behavior and measure its performance through monitoring vital network quality metrics. Divided into three parts, the book offers a review of computer networks and congestion control, presents an adaptive congestion control framework as an alternative to optimization methods, and provides appendices related to dynamic systems through universal neural network approximators.
Reihe
Sprache
Verlagsort
Verlagsgruppe
Zielgruppe
Für höhere Schule und Studium
Illustrationen
105 s/w Abbildungen, 14 s/w Tabellen
14 Tables, black and white; 105 Illustrations, black and white
Maße
Höhe: 234 mm
Breite: 156 mm
Dicke: 18 mm
Gewicht
ISBN-13
978-1-138-07408-8 (9781138074088)
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Schweitzer Klassifikation
Christos N. Houmkozlis is currently in the Department of Electrical and Computer Engineering at Aristotle University of Thessaloniki. His research interests include nonlinear systems, robust adaptive control, modeling and control of communications networks, control over heterogeneous networks, resource management, and pricing in networks.
George A. Rovithakis is Associate Professor in the Department of Electrical and Computer Engineering at Aristotle University of Thessaloniki. His research interests include nonlinear robust adaptive control, neural networks for identification, control of uncertain systems, and control issues arising in computer networks.
Autor*in
Artistotle University of Thessaloniki, Greece
Artistotle University of Thessaloniki, Greece
Introduction. Performance Characteristics. Congestion Control for Best Effort: Internet. End-to-End Congestion Control - A Systems Theory Perspective. Adaptive Control Framework Description: NNRC. NNRC Rate Controller Design. NNRC Fairness Guarantees. NNRC Performance Evaluation. Future Directions. Appendices. References. Index.
