5.2 The Ant-Based Routing System - Durham e-Theses

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Durham E-Theses
Application of ant based routing and intelligent control
to telecommunications network management
Legge, David Nathanial
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Legge, David Nathanial (2006) Application of ant based routing and intelligent control to
telecommunications network management, Durham theses, Durham University. Available at Durham
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2
Application of
Ant Based Routing
and
Intelligent Control
to
Telecommunications Network Management
The copyright of this thesis rests with the
author or the university to which it was
submitted. No quotation from it, or
information derived from it may be published
without the prior written consent of the author
or university, and any information derived
from It should be aclcnowledged.
David Nathanial Legge
School of Engineering
University of Durham
June 2006
A thesis submitted for the degree of
Doctor of Philosophy (PhD)
of the
University of Durham
2 7 JUL 2006
David N. Legge
Application of Ant Based Routing and Intelligent Control to
Telecommunications Network Management
PhD 2004
Abstract
This thesis investigates the use of novel Artificial Intelligence techniques to improve the
control of telecommunications networks. The approaches include the use of Ant-Based
Routing and software Agents to encapsulate learning mechanisms to improve the
performance of the Ant-System and a highly modular approach to network-node
configuration and management into which this routing system can be incorporated.
The management system uses intelligent Agents distributed across the nodes of the
network to automate the process of network configuration. This is important in the
context of increasingly complex network management, which will be accentuated with
the introduction of IPv6 and QoS-aware hardware.
The proposed novel solution allows an Agent, with a Neural Network based Q-Learning
capability, to adapt the response speed of the Ant-System - increasing it to counteract
congestion, but reducing it to improve stability otherwise. It has the ability to adapt its
strategy and learn new ones for different network topologies. The solution has been
shown to improve the performance of the Ant-System, as well as outperform a simple
non-learning strategy which was not able to adapt to different networks.
This approach has a wide region of applicability to such areas as road-traffic
management, and more generally, positioning of learning techniques into complex
domains. Both Agent architectures are Subsumption style, blending short-term
responses with longer term goal-driven behaviour. It is predicted that this will be an
important approach for the application of AI, as it allows modular design of systems in a
similar fashion to the frameworks developed for interoperability of telecommunications
systems.
Declaratlom
I hereby declare that this thesis is a record of work undertaken by myself, that it has not
been the subject of any previous application for a degree, and that all sources of
information have been duly acknowledged.
© 2005. The Copyright of this work rests with the Author. No quotation from it should
be published without their prior written consent and information derived from it should
be acknowledged.
Acknowledgements
I would firstly like to thank Peter Baxendale for his help and support supervising me
over the last few years, and giving me a nudge when I most needed it and Phil Mars for
setting me on the road in the first place.
I would also like to thank the many friends in Durham I have made, all the Andys and
Daves, Richard and the Paul, amongst many others, for their time at local hostelries and
Tony McFarlane for his company in the lab. Further afield my gratitude goes to Spiros,
Malcolm, Daniel and Eduardo, (mostly of York) for their occasional shots of
inspiration.
My immediate family have been behind me all the way, along with my Aunt and Uncle
for looking after me while I was waiting for my house - and countless Sunday lunches
since.
Last but not least, my thanks go to Angela for supporting me, and especially for taking
me to Thailand, where anywhere you stop to sit, you can watch some industrious insects
finding their way around en masse
HI
Contents
Table of Contents
Abstract i
Copyright Declaration ii
Acknowledgements iii
Contents iv
Table of Contents iv
Table of Equations and Figures xii
Nomenclature xvi
Chapter 1: Introduction 1
1.1 Aim of this Thesis 3
1.2 Overview of this Thesis 4
Chapter 2: Network Management and Control 6
2.1 Network Structures 6
2.2 Network Management and Control Defined 9
2.2.1 Functions of Network Management 10
2.2.2 Functions of Network Monitoring 10
2.2.3 Functions of Network Control 10
2.3 Network Monitoring Protocols 11
IV
David Legge Contents
2.3.1 SNMP 12
2.3.2 RMON 13
2.4 Network Control: Routing 13
2.4.1 RIP 14
2.4.2 Open Shortest Path First, OSPF 17
2.4.3 OSPF versus RIP 21
2.4.4 Other Routing Protocols 21
2.5 Admission and Congestion Control 21
2.5.1 Statistical Multiplexing 22
2.5.2 RSVP 23
2.5.3 IPv6 24
2.5.4 ATM Traffic Management 24
2.6 Configuration Complexity 25
2.6.1 DHCP 25
2.6.2 OSPF 26
2.7 Chapter Summary 26
Chapter 3: Intelligent Network Management and Control 28
3.1 A Brief Introduction to Agents 29
3.1.1 Definitions of Agents 31
3.1.2 Properties of Agents 32
3.1.3 Subsumption Architecture 34
3.2 Connection Admission Control Agents 35
3.2.1 Hall 1998 36
3.2.2 Hayzelden 1999 37
3.3 Intelligent Threshold Control 38
3.3.1 Garti and Piyolle 38
3.4 Ant-Based and Intelligent Routing 39
3.4.1 Schoonderwoerd et al 40
David Legge Contents
3.4.2 Heusse et al 41
3.4.3 Bonabeau et al 41
3.4.4 Dorigo et al 42
3.4.5 White et al 42
3.4.6 Choi and Yeung 43
3.4.7 Vittori and Araujo 43
3.5 Failure Recovery Agents 44
3.5.1 Pre-emptive and Dynamic Schemes 44
3.5.2 Link and Node Disjoint Backup Routes 45
3.5.3 General Suitability of Backup Routes 45
3.5.4 Garijo et al 46
3.6 Chapter Summary 46
Chapter 4: Agent System 47
4.1 Overview of the Research 48
4.1.1 Motivations for Research 48
4.1.2 Aims of the Research 49
4.1.3 Major Issues 50
4.2 Research Environment 51
4.2.1 ATM Test-bed 51
4.2.2 BT's Zeus Agent Building Toolkit 52
4.3 Agent Society Structure 53
4.3.1 Analogies for Design of Society 53
4.3.2 Communication Between Agents and Societies 56
4.4 Outline of the Agents 57
4.4.1 Switch Control Agent 57
4.4.2 Neighbour Discovery Agent 58
4.4.3 Network Agent 58
4.4.4 Inter-Society Communication Agent 59
VI
David Legge Contents
4.5 System Development 60
4.5.1 Agent Interfaces 61
4.5.2 Testing Procedures 66
4.5.3 Unit Testing 67
4.5.4 System Testing 69
4.6 Full System Result 69
4.6.1 Test Network 70
4.6.2 Agent Society 70
4.6.3 Output of Agents 71
4.6.4 Discussion of Results 72
4.7 Context for Following Work 73
4.7.1 Failure Recovery Agent 74
4.7.2 DiffServ Agent 75
4.7.3 Link State Routing Agent 75
4.7.4 Ant-Routing System Agent 76
4.7.5 Constraints on Further Work 76
4.8 Chapter Summary 77
Chapter 5:Ant-Based Routing System 79
5.1 Ant-Based Routing: A System Inspired by Nature 79
5.2 The Ant-Based Routing System: Issues In The Design 80
5.2.1 Separation of Ants and Traffic 81
5.2.2 Backward Reinforcement 83
5.2.3 Pheromone Trails and Evaporation 85
5.2.4 The Ant Decides (Randomly) 87
5.2.5 Requirement for Ant Ageing 87
5.2.6 Form of Ant Ageing 89
5.2.7 Ant Production Interval 91
5.2.8 Ant Priority 91
5.2.9 Congestion Compensation 92
vu