Advances in Network Management - Semantic Scholar

Advances in Network Management Jianguo Ding

© 2010 by Taylor and Francis Group, LLC

Auerbach Publications Taylor & Francis Group 6000 Broken Sound Parkway NW, Suite 300 Boca Raton, FL 33487-2742 © 2010 by Taylor and Francis Group, LLC Auerbach Publications is an imprint of Taylor & Francis Group, an Informa business No claim to original U.S. Government works Printed in the United States of America on acid-free paper 10 9 8 7 6 5 4 3 2 1 International Standard Book Number: 978-1-4200-6452-0 (Hardback) This book contains information obtained from authentic and highly regarded sources. Reasonable efforts have been made to publish reliable data and information, but the author and publisher cannot assume responsibility for the validity of all materials or the consequences of their use. The authors and publishers have attempted to trace the copyright holders of all material reproduced in this publication and apologize to copyright holders if permission to publish in this form has not been obtained. If any copyright material has not been acknowledged please write and let us know so we may rectify in any future reprint. Except as permitted under U.S. Copyright Law, no part of this book may be reprinted, reproduced, transmitted, or utilized in any form by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying, microfilming, and recording, or in any information storage or retrieval system, without written permission from the publishers. For permission to photocopy or use material electronically from this work, please access www.copyright.com (http://www.copyright.com/) or contact the Copyright Clearance Center, Inc. (CCC), 222 Rosewood Drive, Danvers, MA 01923, 978-750-8400. CCC is a not-for-profit organization that provides licenses and registration for a variety of users. For organizations that have been granted a photocopy license by the CCC, a separate system of payment has been arranged. Trademark Notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation without intent to infringe. Visit the Taylor & Francis Web site at http://www.taylorandfrancis.com and the Auerbach Web site at http://www.auerbach-publications.com


Contents List of Figures

ix

List of Tables

xiii

Foreword I

xv

Foreword II

xvii

Preface

xxi

About the Author

xxiii

Acknowledgments

xxv

1 Introduction 1.1 Motivation of the Book . . . . . . . . . . . . . . . . . . . . . . 1.2 Structure and Organization of the Book . . . . . . . . . . . . . 2 Evolution of Networks 2.1 Introduction of Networks . . . . . . . . . . . . . . . . 2.1.1 Definition of Networks . . . . . . . . . . . . . . 2.1.2 Network Topologies and Functions . . . . . . . 2.1.3 Types of Networks . . . . . . . . . . . . . . . . 2.2 History of Networks . . . . . . . . . . . . . . . . . . . 2.2.1 History of Telecommunications Networks . . . 2.2.2 History of Computer Networks (Internet) . . . 2.3 Network Architectures . . . . . . . . . . . . . . . . . . 2.3.1 The OSI Reference Model . . . . . . . . . . . . 2.3.2 The TCP/IP Reference Model . . . . . . . . . 2.3.3 Comparison of OSI Model and TCP/IP Model 2.3.4 Evolution of the Internet Protocol (IP) . . . . 2.4 Future of Networks . . . . . . . . . . . . . . . . . . . . 2.4.1 Laws Related to Network Evolution . . . . . . 2.4.2 Trend of Networks . . . . . . . . . . . . . . . .

v © 2010 by Taylor and Francis Group, LLC

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1 1 2 3 3 3 5 10 13 13 16 24 24 28 31 31 36 36 38

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3 Evolution in Network Management 3.1 Introduction of Network Management . . . . . . . . . . . . . . 3.1.1 Definition of Network Management . . . . . . . . . . . . 3.1.2 Basic Components of Network Management System . . 3.2 Network Management Architectures . . . . . . . . . . . . . . . 3.2.1 TMN Management Architecture . . . . . . . . . . . . . 3.2.2 Internet-Based Management Architecture . . . . . . . . 3.2.3 Comparison of TMN- and Internet-Based Management Architecture . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Evolution of Network Management Protocols . . . . . . . . . . 3.3.1 Common Management Information Protocol (CMIP) . . 3.3.2 Simple Network Management Protocol (SNMP) . . . . . 3.3.3 Comparison of SNMP and CMIP . . . . . . . . . . . . . 3.3.4 Internet Protocol Flow Information Export (IPFIX) . . 3.3.5 Network Configuration Protocol (NETCONF) . . . . . . 3.3.6 Syslog . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3.7 Other Protocols Related to Network Management . . . 3.4 Evolution in Network Management Functions . . . . . . . . . . 3.4.1 FCAPS Network Management Functions . . . . . . . . . 3.4.2 Expanded Network Management Functions . . . . . . . 3.4.3 Management Application vs. Management Functionality 3.5 Challenges in Network Management . . . . . . . . . . . . . . .

65 66 67 71 79 81 85 87 89 90 90 95 104 106

4 Theories and Techniques for Network Management 4.1 Policy-Based Network Management . . . . . . . . . . . . . . 4.1.1 Introduction of Policy-Based Management . . . . . . 4.1.2 Policy-Based Management Architecture . . . . . . . 4.1.3 Policy-Based Network Management . . . . . . . . . 4.2 Artificial Intelligence Techniques for Network Management 4.2.1 Expert Systems Techniques . . . . . . . . . . . . . . 4.2.2 Machine Learning Techniques . . . . . . . . . . . . . 4.3 Graph-Theoretic Techniques for Network Management . . . 4.3.1 Causality Graph Model . . . . . . . . . . . . . . . . 4.3.2 Dependency Graph Model . . . . . . . . . . . . . . . 4.3.3 Decision Trees . . . . . . . . . . . . . . . . . . . . . 4.4 Probabilistic Approaches for Network Management . . . . . 4.4.1 Fuzzy Logic . . . . . . . . . . . . . . . . . . . . . . . 4.4.2 Bayesian Networks . . . . . . . . . . . . . . . . . . . 4.5 Web-Based Network Management . . . . . . . . . . . . . . . 4.5.1 Web-Based Network Management . . . . . . . . . . 4.5.2 Web-Based Enterprise Management . . . . . . . . . 4.6 Agent Techniques for Network Management . . . . . . . . . 4.6.1 Introduction of Agent . . . . . . . . . . . . . . . . . 4.6.2 Mobile Agents . . . . . . . . . . . . . . . . . . . . . 4.6.3 Intelligent Agents . . . . . . . . . . . . . . . . . . . .

109 109 109 111 113 116 117 122 133 133 134 135 137 139 140 145 145 146 148 148 151 154


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43 43 43 44 49 50 55

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4.7

Distributed Object Computing for Network Management . . . 158 4.7.1 Introduction of Distributed Object Computing . . . . . 158 4.7.2 Distributed Object Computing for Network Management158 4.8 Active Network Technology for Network Management . . . . . 160 4.8.1 Introduction of Active Network . . . . . . . . . . . . . . 160 4.8.2 Active Network Management . . . . . . . . . . . . . . . 161 4.9 Bio-inspired Approaches . . . . . . . . . . . . . . . . . . . . . . 164 4.9.1 Bio-inspired Computing . . . . . . . . . . . . . . . . . . 164 4.9.2 Bio-inspired Network Management . . . . . . . . . . . . 168 4.10 XML in Network Management . . . . . . . . . . . . . . . . . . 169 4.10.1 Introduction of XML . . . . . . . . . . . . . . . . . . . . 169 4.10.2 XML-Based Network Management . . . . . . . . . . . . 172 4.11 Other Techniques for Network Management . . . . . . . . . . . 173 4.11.1 Economic Theory . . . . . . . . . . . . . . . . . . . . . . 173 4.11.2 Finite-State Machines . . . . . . . . . . . . . . . . . . . 175 4.11.3 Model-Traversing Techniques . . . . . . . . . . . . . . . 176 5 Management of Emerging Networks and Services 5.1 Next Generation Networking . . . . . . . . . . . . . . . 5.1.1 Introduction of Next Generation Networking . . 5.1.2 Management of Next Generation Networking . . 5.2 Wireless Networks . . . . . . . . . . . . . . . . . . . . . 5.2.1 Advances in Wireless Networks . . . . . . . . . . 5.2.2 Mobile Cellular Networks . . . . . . . . . . . . . 5.2.3 Management of Mobile Cellular Networks . . . . 5.2.4 Wireless Ad-Hoc Networks . . . . . . . . . . . . 5.2.5 Management of Wireless Ad-Hoc Networks . . . 5.3 Optical Networks . . . . . . . . . . . . . . . . . . . . . . 5.3.1 Introduction of Optical Networks . . . . . . . . . 5.3.2 Management of Optical Networks . . . . . . . . . 5.4 Overlay Networks . . . . . . . . . . . . . . . . . . . . . . 5.4.1 Management of Peer-to-Peer Networks . . . . . . 5.4.2 Management of VPN (Virtual Private Networks) 5.5 Grid Architectures . . . . . . . . . . . . . . . . . . . . . 5.5.1 Introduction of Grid Networks . . . . . . . . . . 5.5.2 Management of Grid Networks . . . . . . . . . . 5.6 Multimedia Networks . . . . . . . . . . . . . . . . . . . 5.6.1 Introduction of Multimedia Networks . . . . . . 5.6.2 Management of Multimedia Networks . . . . . . 5.7 Satellite Networks . . . . . . . . . . . . . . . . . . . . . 5.7.1 Introduction of Satellite Networks . . . . . . . . 5.7.2 Management of Satellite Networks . . . . . . . . 5.8 Storage Networks . . . . . . . . . . . . . . . . . . . . . . 5.8.1 Introduction of Storage Network . . . . . . . . . 5.8.2 Management of Storage Networks . . . . . . . . .


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179 179 179 183 188 188 192 197 206 223 232 232 236 239 241 249 254 254 257 261 261 262 264 264 267 271 271 274

5.9

Cognitive Networks . . . . . . . . . . . . . . . . . . 5.9.1 Introduction of Cognitive Networks . . . . . 5.9.2 Management of Cognitive Networks . . . . 5.10 Future Internet . . . . . . . . . . . . . . . . . . . . 5.10.1 Introduction of the Internet . . . . . . . . . 5.10.2 Future Internet . . . . . . . . . . . . . . . . 5.10.3 Management Challenges of Future Internet 5.10.4 Management of Future Internet . . . . . . .

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280 280 285 290 290 292 295 296

6 Autonomic Computing and Self-Management 6.1 Autonomic Computing . . . . . . . . . . . . . . . . . . . . 6.1.1 Introduction of Autonomic Computing . . . . . . . 6.1.2 Autonomic Computing Architecture . . . . . . . . 6.1.3 Autonomic System . . . . . . . . . . . . . . . . . . 6.1.4 Autonomic Networks . . . . . . . . . . . . . . . . . 6.2 Context-Aware Management . . . . . . . . . . . . . . . . 6.2.1 Context Awareness . . . . . . . . . . . . . . . . . . 6.2.2 Context-Aware Network . . . . . . . . . . . . . . . 6.3 Self-Management . . . . . . . . . . . . . . . . . . . . . . . 6.3.1 Self-Configuration . . . . . . . . . . . . . . . . . . 6.3.2 Self-Healing . . . . . . . . . . . . . . . . . . . . . . 6.3.3 Self-Optimization . . . . . . . . . . . . . . . . . . . 6.3.4 Self-Protection . . . . . . . . . . . . . . . . . . . . 6.4 Automatic Network Management . . . . . . . . . . . . . . 6.4.1 Network Automation . . . . . . . . . . . . . . . . . 6.4.2 Requirements for Automatic Network Management 6.4.3 Advantages of Automatic Network Management .

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307 307 307 308 309 314 316 316 317 318 318 319 321 322 322 323 324 325

A Standard Organizations and Sections in Network Management

329

B SNMPv3 RFCs

331

C ITU-T TMN M.3000 Series for Network Management

333

D IEEE 802 Working Group and Executive Committee Study Group

335

Abbreviations

337

Bibliography

345


List of Figures 1

IT Complexity and Cost . . . . . . . . . . . . . . . . . . . . . . xvii

2.1 2.2 2.3 2.4 2.5 2.6 2.7 2.8 2.9 2.10 2.11 2.12 2.13 2.14 2.15 2.16 2.17

A Classification of Communication Networks . . . . . . . Bus Topology . . . . . . . . . . . . . . . . . . . . . . . . . Star Topology . . . . . . . . . . . . . . . . . . . . . . . . . Tree Topology . . . . . . . . . . . . . . . . . . . . . . . . . Ring Topology . . . . . . . . . . . . . . . . . . . . . . . . Fully Connected Topology . . . . . . . . . . . . . . . . . . Hybrid Topology . . . . . . . . . . . . . . . . . . . . . . . Mesh Topology . . . . . . . . . . . . . . . . . . . . . . . . The Growth of Internet Hosts and Web Hosts . . . . . . . The Growth of Internet Users . . . . . . . . . . . . . . . . Internet Users in the World by Geographic Regions . . . . World Internet Penetration Rates by Geographic Regions OSI Reference Model . . . . . . . . . . . . . . . . . . . . . TCP/IP Reference Model . . . . . . . . . . . . . . . . . . Moore’s Law . . . . . . . . . . . . . . . . . . . . . . . . . Gilder’s Law . . . . . . . . . . . . . . . . . . . . . . . . . Metcalfe’s Law . . . . . . . . . . . . . . . . . . . . . . . .

3.1 3.2 3.3 3.4 3.5 3.6 3.7 3.8 3.9 3.10

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ASN.1 Object Identifier Organized Hierarchically . . . . . . . . The Typical Network Management Architecture . . . . . . . . . General Relationship of a TMN to a Telecommunication Network TMN Function Blocks . . . . . . . . . . . . . . . . . . . . . . . Example of Reference Points between Function Blocks . . . . . TMN Defined Multiple Related Architecture . . . . . . . . . . Relation between TMN Architectures . . . . . . . . . . . . . . A Managed Object . . . . . . . . . . . . . . . . . . . . . . . . . Management Layer Model and Function Areas . . . . . . . . . Components of the TCP/IP Internet Standard Management Framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.11 SNMP Operational Model . . . . . . . . . . . . . . . . . . . . . 3.12 RMON MIB Tree Diagram . . . . . . . . . . . . . . . . . . . . 3.13 The Work Layers of RMON1 and RMON2 . . . . . . . . . . . .

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3.14 3.15 3.16 3.17 3.18 3.19 3.20 3.21 3.22 3.23 3.24

CMIP on the OSI Management Architecture . . . . . . . . The CMOT Protocol Architecture . . . . . . . . . . . . . . SNMP Protocol . . . . . . . . . . . . . . . . . . . . . . . . . SNMPv3 Entity . . . . . . . . . . . . . . . . . . . . . . . . . IPFIX Architecture . . . . . . . . . . . . . . . . . . . . . . . Layers of NETCONF . . . . . . . . . . . . . . . . . . . . . . The Relationship of Device, Relay, and Collector for Syslog SLA Management Process Model . . . . . . . . . . . . . . . Change Management Process . . . . . . . . . . . . . . . . . Model of Situation Management . . . . . . . . . . . . . . . Situation Management Framework . . . . . . . . . . . . . .

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69 71 73 77 83 86 88 97 101 102 103

4.1 4.2 4.3

Classification of Network Management Techniques . . . . . . . The IETF Policy-Based Management Architecture . . . . . . . PBNM Automated Configuration/Change Management in an Integrated Environment . . . . . . . . . . . . . . . . . . . . . . Expert System Functional Diagram . . . . . . . . . . . . . . . . Model of a Feedforward Neural Network . . . . . . . . . . . . . Causality Graph . . . . . . . . . . . . . . . . . . . . . . . . . . Example of a Decision Tree . . . . . . . . . . . . . . . . . . . . Basic Model of Bayesian Networks . . . . . . . . . . . . . . . . An Example of a Bayesian Network in Network Management . Web-Based Network Management . . . . . . . . . . . . . . . . . Web-Based Enterprise Management . . . . . . . . . . . . . . . A Framework of a Mobile Agent-Based Distributed Network Management System . . . . . . . . . . . . . . . . . . . . . . . . Framework of Intelligent Agents . . . . . . . . . . . . . . . . . . Active Network Framework . . . . . . . . . . . . . . . . . . . . Packet Flow through an Active Node . . . . . . . . . . . . . . . Bio-inspired Architecture for Network Management . . . . . . . Application Architecture of Bio-inspired Self-Management . . . XML-based Combinations of Manager and Agent . . . . . . . . Architecture of an XML-Based Manager . . . . . . . . . . . . . Architecture of an XML-Based Agent . . . . . . . . . . . . . . Architecture of an XML/SNMP Gateway . . . . . . . . . . . .

110 112

4.4 4.5 4.6 4.7 4.8 4.9 4.10 4.11 4.12 4.13 4.14 4.15 4.16 4.17 4.18 4.19 4.20 4.21 5.1 5.2 5.3 5.4 5.5 5.6 5.7

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116 117 131 134 137 142 144 147 149 153 156 162 163 170 171 173 173 174 175

NGN Architecture Overview . . . . . . . . . . . . . . . . . . . . 180 NGN Components and Internet Protocol Reference Model Layers182 Example of NGN Realization . . . . . . . . . . . . . . . . . . . 183 eTOM Business Process Framework . . . . . . . . . . . . . . . 186 Classification of Wireless Networks . . . . . . . . . . . . . . . . 189 Wireless Networks Technologies Based on IEEE Standards . . . 190 Future Wireless Communications: An All – Encompassing Network of Networks . . . . . . . . . . . . . . . . . . . . . . . . . . 190


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A Classification of Short-Range Communications According to the Typical Supported Range . . . . . . . . . . . . . . . . . . . A General Classification of Short-range Communications . . . . A Vision for 4G Wireless Communications in Terms of Mobility Support and Data Transmission Rate . . . . . . . . . . . . . . . Architecture of Wireless Mesh Networks . . . . . . . . . . . . . Overview of a Backbone Mesh Network and Connections to WiFi, WiMAX, and Wireless Cellular Networks . . . . . . . . . Connectivity between a Backbone Wireless Mesh Network to Wireless Users and Other Networking Devices . . . . . . . . . . Architecture for Applications of Wireless Sensor Networks . . . Overview of an Optical Network . . . . . . . . . . . . . . . . . Typical Optical Network . . . . . . . . . . . . . . . . . . . . . . An Overlay Network for Connections Between LANs . . . . . . Client/Server Model and P2P Model . . . . . . . . . . . . . . . Centralized Architecture of P2P . . . . . . . . . . . . . . . . . Decentralized Architecture of P2P . . . . . . . . . . . . . . . . Hybrid Architecture of P2P . . . . . . . . . . . . . . . . . . . . An Example of VPN Through a Tunnel Using Public Facilities Job Management in a Grid . . . . . . . . . . . . . . . . . . . . Sample Applications of a Satellite Network . . . . . . . . . . . SAN vs. NAS vs. DAS . . . . . . . . . . . . . . . . . . . . . . . Organization of SAN, NAS, and DAS . . . . . . . . . . . . . . Storage Network with NAS and SAN . . . . . . . . . . . . . . . Cognitive Radio Network Architecture . . . . . . . . . . . . . . An Example of Cognitive Network Functionality . . . . . . . . Spectrum Management Framework for Cognitive Networks . . A Model for Location Information Management in Cognitive Networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Future Internet Capabilities . . . . . . . . . . . . . . . . . . . .

6.1 6.2 6.3

Conceptual Model of an Autonomic System . . . . . . . . . . . 310 Autonomic Computing Reference Architecture . . . . . . . . . 312 Functional Details of an Autonomic Manager . . . . . . . . . . 313

5.9 5.10 5.11 5.12 5.13 5.14 5.15 5.16 5.17 5.18 5.19 5.20 5.21 5.22 5.23 5.24 5.25 5.26 5.27 5.28 5.29 5.30 5.31


191 191 198 219 220 221 222 233 235 240 241 243 244 245 250 260 266 273 274 275 283 284 287 289 297

List of Tables 2.1

Statistics of Internet Hosts and Web Hosts . . . . . . . . . . . . 22

3.1 3.2 3.3 3.4

SNMP Manager Operations . . . A Detailed Comparison of SNMP IPFIX Information . . . . . . . . IPFIX Message . . . . . . . . . .

4.1

Summary of Machine Learning Problem Formulations . . . . . 125

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Foreword I

Like computer security, network management is a latent issue that computer and network users tend to ignore—until a disruption occurs. But today’s business applications depend on reliable, secure, and well-performing networked computer infrastructures that may span large geographical areas and a multitude of management domains. Such infrastructures constantly change because hardware and software components are replaced or updated, new components are added, and old ones are shut down. In addition, hardware is subject to degradation and failure, software components give rise to faults, and the network may exhibit performance bottlenecks. It is obvious that successful network management plays a crucial economic role. System administrators have a variety of hardware and software tools available to monitor the resources in their management domain and to help in diagnosing and reacting to defects—often after the fact. However, it would not be much more effective when potential hardware and software malfunctions, failures, and other threads could be foreseen and protective measures could be taken before they can occur? The growing complexity of today’s distributed computing infrastructures requires innovative predictive techniques and self-managing mechanisms. Although network management came to life in AT&T’s telecommunications network already in 1920, this book is timely in addressing a contemporary view on network management. The book provides insight into fundamental concepts of network management. It presents a range of theories and practical techniques for network management and discusses advanced networks and network services. The final chapter covers advanced paradigms such as autonomic computing, context-aware systems management and automatic techniques aiming at self-management, self-(re)configuration, selfoptimization, self-healing, or self-protection. Autonomic computing deals with the increasing difficulty of managing distributed computing systems, which become more and more interconnected and diverse, and software applications that go beyond corporate boundaries into the Internet. Autonomic computing anticipates systems consisting of myriads of interacting autonomous components that are able to manage themselves according to predefined goals and policies. Context-aware systems management aims to take the availability of dynamically changing resources and services during a particular period of system operation into account. Management policies and automated mechanisms need to be able to adapt to dynamic changes such that they offer the best possible level of service to the user in the given situation. Self-management capabilities include automated configuration of components, automated recognition of opportunities for performance improvement (self-optimization), automatic detection, diagnosis and repair of local hardware and software problems, and automatic defense against attacks. The xv © 2010 by Taylor and Francis Group, LLC

Foreword I

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objective is to minimize the degree of external intervention, e.g., by human system managers, and, at the same time, to preserve the architectural properties imposed by its specification. The concept of self-configuration refers to a process in which an application’s internal structure changes depending on its environment. With its breadth and depth in theoretical, technical, and research topics, the book serves well as an account of both the state-of-technique and stateof-the-art in a very important and current research area. Prof. Dr.-Ing. Bernd J. Kr¨ amer FernUniversität in Hagen, Germany April 2009


Foreword II The Challenges of IT Investments: Management and Sustainability It is very challenging to find stats that clearly spell out the bigger picture of IT investments and the impact on their management and maintenance. The only relevant stats that summoned the issue very well was one from Jawad Khaki, VP at Microsoft responsible for networking where he shows that the US business volume of hardware and software has massively shrunk over the past two decades from $200 billion down to $60 billion, while the cost of management and support has exploded from less that $20 billion to $140 billion. 70% of it is spent on the management and maintenance of the legacy networks and only 30% is spent on managing new networks.

Figure 1: IT Complexity and Cost The only other sector that has a similar picture is the airlines sector, although there are less planes crashing daily than servers and computer systems. The airlines sector has the stringent safety and security standards to follow, making air transportation the safest sector, at least compared to the automobile sector. However, if the same safety and security standards were applied to the IT sector, then either the investment in management and maintenance would be dramatically increased and make the computer sector inefficient or the IT sector would need to re-think its way forward on how to limit the explosion of its sustainability costs. The deeper impact of such a picture has significant strategic implications on the IT sector. The CTOs are absorbed more in day-to-day functions and lose the strategic thinking about introducing new technologies and new efficiencies. xvii © 2010 by Taylor and Francis Group, LLC

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The outsourcing of tedious tasks have resolved some issues but introduced new ones as well, such as making the introduction of new technologies very difficult because the outsourcer would tag the new technologies at a higher price. The discussions among the researchers to simplify management or even to enable self-management or discuss implementation of autonomicity in networks have been one of the favorite research topics because the benefits are quite evident. The commoditization of networking going into every sector and even to the home is racing in front of us. The Internet has reached a high level of penetration, between 50% and 75% in Europe and in the US. This makes the Internet the next technology to become a utility with over 1.5 billion users around the world. Cell phones are used now by over 4.0 billion users, although 10% of them are smart phones using Internet services. This level of penetration will put a lot more pressure on the management and maintenance on the networking side. Network management is a domain plagued by proprietary solutions and some oligopolistic solutions. The industry should strive to create open source network management solutions that allow for easier integration of all vendors and applications developers. Another approach to use in parallel is to define generic autonomic network architectures (GANA) such as those defined by the Autonomic Future Internet (AFI) Industry Specification Group under the auspices of ETSI (the European Telecommunications Standards Institute) coordinated by the EU-funded project EFIPSANS (Exposing the Features in IP version Six protocols that can be exploited /extended for the purposes of designing / building Autonomic Networks and Services). AFI is working on the GANA vision to enable self-management concepts that will allow for the next step in self-managed networks, a promising path for this complex and legacy-plagued networking industry. AFI is now calling for contributions to the GANA specifications, and the definition of an evolutionary path toward self-managing future multi-services (i.e., Future Internet), from Future Internet research architects across the globe. One of the new key technologies that needs close attention is the new Internet Protocol version 6 (IPv6). The deployment of IPv6 has become an issue of strategic importance for many economies. Enterprise networks and ISPs play a key role in ensuring the availability of this new protocol on their networks. It cannot be denied that the complexities exist in deploying IPv6 in an IPv4 world. Knowing this, telecom operators and ISPs have to ensure a viable transition strategy that takes into account transparent interoperability and mature integrated functionalities for deploying advanced applications on both IPv4 and IPv6. This potent combination will enable operators and ISPs to exploit the richer services offered by IPv6 while interoperating with IPv4 during this long transition period, creating new business models that will generate return on investment without waiting for the whole world to be fully IPv6 deployed. The management using IPv6 will be a lot more transparent to the network administrators as the reachability of any node on the network is


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an essential element in his work to check on each device, to update its security, and to manage it from any remote place. The author raises essential issues at stake and brings the necessary expertise and experience identifying the challenges and proposing recommendations of great value to a world made of heterogeneous and widely uninteroperable networks designed with private addressing schemes that inhibit end-to-end management and end-to-end services. Latif Ladid President, IPv6 Forum September 2009


Preface

Network management is facing new challenges, stemming from the growth in size, heterogeneity, pervasiveness, complexity of applications, network services, the combination of rapidly evolving technologies, and increased requirements from corporate customers. Over a decade ago, the classic agent-manager centralized paradigm was the prevalent network management architecture, exemplified in the OSI reference model, the Simple Network Management Protocol (SNMP), and the Telecommunications Management Network (TMN) management framework. The increasing trend toward enterprise application integration based on loosely coupled heterogeneous IT infrastructures forces a change in management paradigms from centralized and local to distributed management strategies and solutions that are able to cope with multiple autonomous management domains and possibly conflicting management policies. In addition, serviceoriented business applications come with end-to-end application-level quality of service (QoS) requirements and service-level agreements (SLA) that depend on the qualities of the underlying IT infrastructure. More recently, requirements in network management and control have been amended by emerging network and computing models, including wireless networks, ad hoc networks, overlay networks, Grid networks, optical networks, multimedia networks, storage networks, the convergence of next generation networks (NGN), or even nanonetworks, etc. Increasingly ubiquitous network environments require new management strategies that can cope with resource constraints, multi-federated operations, scalability, dependability, context awareness, security, mobility, and probability, etc. A set of enabling technologies are recognized to be potential candidates for distributed network management, such as policy-based management strategies, artificial intelligence techniques, probabilistic approaches, web-based techniques, agent techniques, distributed object computing technology, active networks technology, bio-inspired approach, or economic theory, etc. To bring complex network systems under control, it is necessary for the IT industry to move to autonomic management, context-aware management, and selfmanagement systems in which technology itself is used to manage technology. This book documents the evolution of networks and the trends, the evolution of network management solutions in network management paradigms, protocols, and techniques. It also investigates novel management strategies for emerging networks. The areas covered range from basic concepts to researchlevel material, including future directions. The targeted audience for this book includes researchers (faculty members, PhD students, graduate students, senior undergraduates); professionals who are working in the area of network management; engineers who are designers or planners for network management systems; and those who would like to learn about this field. xxi © 2010 by Taylor and Francis Group, LLC