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Library | Item Barcode | Call Number | Material Type | Item Category 1 | Status |
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Searching... | 30000010324849 | TK5102.985 H68 2012 | Open Access Book | Book | Searching... |
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Summary
Summary
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 presentedDrawing 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.
Author Notes
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.
Table of Contents
List of Figures | p. xiii |
List of Tables | p. xix |
Preface | p. xxi |
1 Introduction | p. 1 |
1.1 Overview | p. 1 |
1.2 Future Internet | p. 2 |
1.3 Internet Congestion Control | p. 4 |
1.4 Adaptive Congestion Control | p. 8 |
I Background on Computer Networks and Congestion Control | p. 13 |
2 Controlled System: The Packet-Switched Network | p. 15 |
2.1 Overview | p. 15 |
2.2 Network Connectivity | p. 17 |
2.2.1 Links and Nodes | p. 17 |
2.2.2 Sub-Networks | p. 17 |
2.2.3 Network Classification | p. 19 |
2.2.4 LAN Topologies | p. 21 |
2.3 Network Communication | p. 24 |
2.3.1 Packet Switching | p. 24 |
2.3.2 Protocols and Layering | p. 26 |
2.3.3 Internet Architecture | p. 28 |
2.3.4 Transfer Control Protocol (TCP) | p. 32 |
2.3.5 User Datagram Protocol (UDP) | p. 37 |
2.3.6 Internet Protocol (IP) | p. 38 |
2.4 Performance Characteristics | p. 40 |
2.4.1 Queue Size | p. 40 |
2.4.2 Throughput | p. 41 |
2.4.3 Link Utilization | p. 41 |
2.4.4 Packet Loss Rate | p. 41 |
2.4.5 Round Trip Time | p. 41 |
2.4.6 Fairness | p. 42 |
2.5 Applications | p. 43 |
2.5.1 E-Mail | p. 44 |
2.5.2 World Wide Web | p. 44 |
2.5.3 Remote Access | p. 45 |
2.5.4 File Transfer | p. 45 |
2.5.5 Streaming Media | p. 46 |
2.5.6 Internet Telephony (VOIP) | p. 46 |
2.6 Concluding Comments | p. 47 |
3 Congestion Issues and TCP | p. 49 |
3.1 Overview | p. 49 |
3.2 Core Issues in Congestion Control | p. 50 |
3.3 TCP: Flow Control and Congestion Control | p. 51 |
3.3.1 Slow Start | p. 52 |
3.3.2 Congestion Avoidance | p. 53 |
3.3.3 Fast Retransmit and Fast Recovery | p. 55 |
3.4 TCP Problems | p. 57 |
3.5 Managing Congestion | p. 59 |
3.5.1 TCP Friendliness | p. 59 |
3.5.2 Classification of Congestion Control Protocols | p. 60 |
3.5.2.1 Window-Based vs. Rate-Based | p. 60 |
3.5.2.2 Unicast vs. Multicast | p. 61 |
3.5.2.3 End-to-End vs. Router-Based | p. 62 |
3.6 Concluding Comments | p. 63 |
4 Measuring Network Congestion | p. 65 |
4.1 Overview | p. 65 |
4.2 Drop Tail | p. 66 |
4.3 Congestion Early Warning | p. 67 |
4.3.1 Packet Drop Schemes | p. 68 |
4.3.2 Packet Marking Schemes | p. 72 |
4.4 Concluding Comments | p. 77 |
5 Source-Based Congestion Control Mechanisms | p. 79 |
5.1 Overview | p. 79 |
5.2 Traditional TCP | p. 80 |
5.3 TCP Modifications for Networks with Large Bandwidth Delay Products | p. 81 |
5.3.1 Scalable TCP (STCP) | p. 82 |
5.3.2 HighSpeed TCP (HSTCP) | p. 82 |
5.3.3 BIC | p. 84 |
5.3.4 CUBIC | p. 85 |
5.4 Delay-Based Congestion Control | p. 86 |
5.4.1 TCP Vegas | p. 87 |
5.4.2 FAST TCP | p. 88 |
5.5 Congestion Control for Wireless Networks | p. 89 |
5.5.1 TCP Westwood | p. 90 |
5.5.2 TCP Veno | p. 91 |
5.6 Congestion Control for Multimedia Applications | p. 92 |
5.6.1 Rate Adaptation Protocol (RAP) | p. 92 |
5.6.2 TFRC | p. 94 |
5.7 Concluding Comments | p. 95 |
6 Fluid Flow Model Congestion Control | p. 97 |
6.1 Overview | p. 97 |
6.2 The Fluid Flow Model | p. 98 |
6.3 Network Representation | p. 99 |
6.4 Congestion Control as a Resource Allocation Problem | p. 101 |
6.4.1 Dual Approach | p. 103 |
6.4.2 Primal Approach | p. 104 |
6.4.3 Utility Function Selection | p. 104 |
6.5 Open Issues | p. 106 |
6.5.1 Stability and Convergence | p. 106 |
6.5.2 Implementation Constraints | p. 107 |
6.5.3 Robustness | p. 107 |
6.5.4 Fairness | p. 108 |
6.6 Concluding Comments | p. 109 |
II Adaptive Congestion Control Framework | p. 111 |
7 NNRC: An Adaptive Congestion Control Framework | p. 113 |
7.1 Overview | p. 113 |
7.2 Packet Switching Network System | p. 114 |
7.3 Problem Statement | p. 117 |
7.4 Throughput Improvement | p. 118 |
7.5 NNRC Framework Description | p. 120 |
7.5.1 Future Path Congestion Level Estimator | p. 121 |
7.5.2 Feasible Desired Round Trip Time Estimator | p. 122 |
7.5.3 Rate Control | p. 122 |
7.5.4 Throughput Control | p. 123 |
7.6 Concluding Comments | p. 123 |
8 NNRC: Rate Control Design | p. 125 |
8.1 Overview | p. 125 |
8.2 Feasible Desired Round Trip Time Estimator Design | p. 125 |
8.2.1 Proof of Lemma 8.1 | p. 129 |
8.2.2 Proof of Lemma 8.2 | p. 130 |
8.3 Rate Control Design | p. 132 |
8.3.1 Guaranteeing Boundness of Transmission Rate | p. 137 |
8.3.2 Reducing Rate in Congestion | p. 138 |
8.4 Illustrative Example | p. 140 |
8.4.1 Implementation Details | p. 141 |
8.4.2 Network Topology | p. 142 |
8.4.3 Normal Scenario | p. 142 |
8.4.4 Congestion Avoidance Scenario | p. 143 |
8.5 Concluding Comments | p. 148 |
9 NNRC: Throughput and Fairness Guarantees | p. 151 |
9.1 Overview | p. 151 |
9.2 Necessity for Throughput Control | p. 151 |
9.3 Problem Definition | p. 153 |
9.4 Throughput Control Design | p. 154 |
9.4.1 Guaranteeing Specific Bounds on the Number of Channels | p. 156 |
9.4.2 Reducing Channels in Congestion | p. 157 |
9.5 Illustrative Example | p. 158 |
9.5.1 Implementation Details | p. 159 |
9.5.2 Normal Scenario | p. 160 |
9.5.3 Congestion Avoidance Scenario | p. 163 |
9.5.4 Throughput Improvement | p. 163 |
9.6 Concluding Comments | p. 169 |
10 NNRC: Performance Evaluation | p. 171 |
10.1 Overview | p. 171 |
10.2 Network Topology | p. 172 |
10.3 Scalability | p. 174 |
10.3.1 Effect of Maximum Queue Length | p. 174 |
10.3.2 Effect of Propagation Delays | p. 176 |
10.3.3 Effect of Bandwidth | p. 178 |
10.4 Dynamic Response of NNRC and FAST TCP | p. 180 |
10.4.1 Bursty Traffic | p. 182 |
10.4.2 Re-Routing | p. 183 |
10.4.3 Non-Constant Number of Sources | p. 186 |
10.5 NNRC and FAST TCP Interfairness | p. 188 |
10.6 Synopsis of Results | p. 199 |
10.7 Concluding Comments | p. 200 |
11 User QoS Adaptive Control | p. 203 |
11.1 Overview | p. 203 |
11.2 Application Adaptation Architecture | p. 204 |
11.2.1 QoS Mapping | p. 204 |
11.2.2 Application QoS Control Design | p. 205 |
11.3 NNRC Source Enhanced with Application Adaptation | p. 207 |
11.4 Illustrative Example | p. 208 |
11.4.1 Application Adaptation Implementation Details | p. 209 |
11.4.2 Simulation Study | p. 210 |
11.5 Concluding Comments | p. 210 |
III Appendices | p. 215 |
A Dynamic Systems and Stability | p. 217 |
A.1 Vectors and Matrices | p. 217 |
A.1.1 Positive Definite Matrices | p. 219 |
A.2 Signals | p. 221 |
A.3 Functions | p. 223 |
A.3.1 Continuity | p. 223 |
A.3.2 Differentiation | p. 224 |
A.3.3 Convergence | p. 225 |
A.3.4 Function Properties | p. 226 |
A.4 Dynamic Systems | p. 227 |
A.4.1 Stability Definitions | p. 229 |
A.4.2 Boundedness Definitions | p. 231 |
A.4.3 Stability Tools | p. 232 |
B Neural Networks for Function Approximation | p. 247 |
B.1 General | p. 247 |
B.2 Neural Networks Architectures | p. 249 |
B.2.1 Multilayer Perceptron (MLP) | p. 250 |
B.2.2 Radial Basis Function Networks (RBF) | p. 252 |
B.2.3 High-Order Neural Networks (HONN) | p. 253 |
B.3 Off-Line Training | p. 255 |
B.3.1 Algorithms | p. 257 |
B.3.1.1 Gradient Algorithms | p. 257 |
B.3.1.2 Least Squares | p. 261 |
B.3.1.3 Backpropagation | p. 262 |
B.4 On-Line Training | p. 263 |
B.4.1 Filtering Schemes | p. 263 |
B.4.1.1 Filtered Error | p. 264 |
B.4.1.2 Filtered Regressor | p. 265 |
B.4.2 Lyapunov-Based Training | p. 266 |
B.4.2.1 LIP Case | p. 266 |
B.4.2.2 NLIP Case | p. 266 |
B.4.3 Steepest Descent Training | p. 267 |
B.4.4 Recursive Least Squares Training | p. 268 |
B.4.5 Robust On-Line Training | p. 269 |
Bibliography | p. 273 |
Index | p. 301 |