by Wong Leung-Chung Chris. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1997. / Includes bibliographical references (leaves 86-[92]). / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Routing Overview --- p.2 / Chapter 1.2 --- Routing in the Internet --- p.5 / Chapter 1.2.1 --- Inter-Domain Routing --- p.6 / Chapter 1.2.2 --- Intra-Domain Routing --- p.7 / Chapter 1.2.3 --- The Future Trend --- p.7 / Chapter 2 --- Inter-Domain Routing --- p.9 / Chapter 2.1 --- Inter-Domain Routing Protocols --- p.9 / Chapter 2.1.1 --- Exterior Gateway Protocol (EGP) --- p.10 / Chapter 2.1.2 --- Border Gateway Protocol (BGP) --- p.11 / Chapter 2.1.3 --- Inter-Domain Policy Routing (IDPR) --- p.12 / Chapter 2.1.4 --- Other Protocols --- p.13 / Chapter 2.2 --- The Need for Pricing on Inter-Domain Routing Protocols --- p.13 / Chapter 2.3 --- Pricing Scheme on the Inter-Domain level --- p.15 / Chapter 2.4 --- Routing Protocols to Support Pricing on the Internet --- p.16 / Chapter 2.4.1 --- Routing Towards Multiple-Additive Metrics --- p.16 / Chapter 2.4.2 --- "Network Model, Notations and Assumptions" --- p.16 / Chapter 2.4.3 --- The Problem Statement --- p.18 / Chapter 3 --- Application of Neural Nets in Route Selection --- p.20 / Chapter 3.1 --- Neural Network (NN) Overview --- p.20 / Chapter 3.1.1 --- Brief History on Neural Network Research --- p.20 / Chapter 3.1.2 --- Definition of Neural Network --- p.21 / Chapter 3.1.3 --- Neural Network Architectures --- p.22 / Chapter 3.1.4 --- Transfer Fucntion of a Neuron --- p.24 / Chapter 3.1.5 --- Learning Methods --- p.25 / Chapter 3.1.6 --- Applications in Telecommunications --- p.26 / Chapter 3.2 --- Review on the Applications of Neural Networks in Packet Routing --- p.27 / Chapter 3.2.1 --- The JEB Branch --- p.27 / Chapter 3.2.2 --- The Hopfield/Energy Minimization Branch (HEM) --- p.29 / Chapter 3.2.3 --- Supervised Learning (SL) --- p.34 / Chapter 3.3 --- Discussions --- p.35 / Chapter 4 --- Route Selection as “Link-state´ح Classification --- p.36 / Chapter 4.1 --- Multi-Layer Feedforward Network (MLFN) --- p.37 / Chapter 4.1.1 --- Function Approximation Power of MLFN --- p.38 / Chapter 4.1.2 --- Choosing MLFN parameters..........´ب --- p.40 / Chapter 4.1.3 --- Trailing a MLFN --- p.41 / Chapter 4.2 --- The Utility Function --- p.43 / Chapter 4.3 --- The Neural Network Architecture --- p.46 / Chapter 4.3.1 --- Routing Graph Representation with Successor Sequence Table (SST) --- p.46 / Chapter 4.3.2 --- The Neural Network Layout --- p.52 / Chapter 4.3.3 --- How the Neural Network Controller Works --- p.55 / Chapter 4.3.4 --- Training --- p.56 / Chapter 4.4 --- Simulation --- p.56 / Chapter 4.4.1 --- Performance Parameters --- p.56 / Chapter 4.4.2 --- Simulation Results --- p.57 / Chapter 4.5 --- Conclusions and Discussions --- p.70 / Chapter 5 --- Route Selection as Energy Minimization - A Theoretical Study --- p.73 / Chapter 5.1 --- The Hopfield/Tank NN Model --- p.73 / Chapter 5.2 --- Boltzman's Machine --- p.76 / Chapter 5.3 --- Boltzman's Machine Model for Multiple-Metrices Routing --- p.79 / Chapter 5.4 --- Conclusions --- p.82 / Chapter 6 --- Conclusions --- p.84 / Bibliography --- p.86
| Identifer | oai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_321942 |
| Date | January 1997 |
| Contributors | Wong, Leung-Chung Chris., Chinese University of Hong Kong Graduate School. Division of Information Engineering. |
| Source Sets | The Chinese University of Hong Kong |
| Language | English |
| Detected Language | English |
| Type | Text, bibliography |
| Format | print, viii, 86, [6] leaves : ill. ; 30 cm. |
| Rights | Use of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/) |
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