Agrégation et routage de trafic dans les réseaux WDM multi-couches.

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Doumith, Elias (2007) Agrégation et routage de trafic dans les réseaux WDM multi-couches. Doctorat Informatique et réseaux, Informatique et Réseaux, ENST p.255.

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Résumé

Les réseaux de transport haut-débit doivent être capable de pouvoir transporter à la fois différents types de trafic ; permanent, planifié, sporadique, et même aléatoire. En général, de tels réseaux sont déployés en utilisant une infrastructure optique offrant des canaux de transmission permettant des débits de plusieurs Gigabits par seconde. Cependant, la plupart des applications actuellement existantes exigent une bande passante inférieure à celle-ci, d'où la nécessité de pouvoir agréger plusieurs demandes sur le même canal optique. Il est donc important que ces réseaux soient conçus de manière optimale en termes de coût tout en permettant le transport efficace de ces types de trafic. Cette thèse porte sur la conception et l'analyse de réseaux optiques permettant l'ingénierie de trafic englobant les fonctions d'agrégation et de reroutage. Dans notre étude, nous considérons simultanément des demandes de trafic déterministes et d'autres aléatoires. Dans un premier temps, une solution exacte ainsi qu'une approche heuristique sont développées pour le problème de dimensionnement de réseaux multi-granulaires dans le cas de demandes déterministes. Dans un deuxième temps, le problème de routage et d'agrégation dynamique des demandes aléatoires est examiné sous réserve de la disponibilité de ressources libres dans le réseau. Plusieurs algorithmes sont développés pour faciliter ce problème de provisionnement. Enfin, des techniques de reroutage de trafic sont abordées. Nous étudions différentes stratégies de reroutage et leur application en vue d'améliorer l'efficacité du réseau quand ce dernier transporte à la fois des demandes de trafic planifiées et d'autres aléatoires.

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Books



[B150] K. Zhu, H. Zhu, and B. Mukherjee. Traffic Grooming in Optical WDM Mesh Networks. Springer Science + Business Media, Inc., New York, NY 10013, USA, 2005.

[B151] J.-P. Vasseur, M. Pickavet, and P. Demeester. Network Recovery: Protection and Restoration of Optical, SONET-SDH, IP, and MPLS. Morgan Kaufmann Publishers, San Francisco, CA 94111, USA, 2004.

[B152] B. Mukherjee. Optical WDM Networks. Springer Science + Business Media, Inc., New York, NY 10013, USA, 2006.

[B153] R. Ramaswami, and K. N. Sivarajan. Optical Networks: A Practical Perspective. Morgan Kaufmann Publishers, San Francisco, CA 94104, USA, 2002.

[B154] T. M. Cover, and J. A. Thomas. Elements of Information Theory. John Wiley & Sons, Inc., Hoboken, NJ 07030, USA, 2006.



Books



[D155] A. Gençata. Topology and Bandwidth Adaptation in Optical WDM Backbone Networks with Dynamic Traffic. PhD thesis, Istanbul Technical University, 2003.

[D156] J. Kuri. Optimization Problems in WDM Optical Transport Networks with Scheduled Lightpath Demands. PhD thesis, Ecole Nationale Supérieure des Télécommunications, 2003.

[D157] S. Ramamurthy. Optical Design of WDM Network Architectures. PhD thesis, University of California, Davis, 1998.

[D158] A. R. Lehman. Network Coding. PhD thesis, Massachusetts Institute of Technology, 2005.



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[W162] National Science Foundation Website: A brief history of NSF and the Internet. http://www.nsf.gov/news/news_summ.jsp?cntn_id=103050.

[W163] National Laboratory for Applied Network Research, Measurement and Network Analysis Group. http://www.ntu.edu.sg/home5/PG01080112/.

[W164] Pew Internet & American Life Project Website. http://www.pewinternet.org.

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[W167] IETF Working Group Website: Path Computation Element (PCE). http://www.ietf.org/html.charters/pce-charter.html.

[W168] ILOG CPLEX Website. http://www.ilog.com/products/cplex/.

[W169] Sandia National Laboratories Website: A survey of global optimization methods. http://www.cs.sandia.gov/opt/survey/main.html.

[W170] U.S. National Institute of Standards and Technology Website: Dictionary of algorithms and data structures. http://www.nist.gov/dads/.

[W171] Open Grid Forum Website. http://www.ogf.org/index.php.

[W172] TeraGyroid Project Website: Grid-based lattice-Boltzmann simulations of defect dynamics in amphiphilic liquid crystals. http://www.realitygrid.org/TeraGyroid/.

[W173] TeraGrid Project Website. http://www.teragrid.org/.

[W174] Research Councils UK Website: About the UK e-Science programme. http://www.rcuk.ac.uk/escience/.

[W175] SURFnet Website: High-quality Internet for higher education and research. http://www.surfnet.nl/info/en/home.jsp.

[W176] Advanced Radio-Optics Integrated Technology (ADROIT) Group Website. http://www.rnet.ryerson.ca/adroit/.

[W177] The 3rd Generation Partnership Project (3GPP) Website. http://www.3gpp.org/.



Personal Publications



[1] M. Gagnaire, and E. A. Doumith are co-authors of a chapter to appear in Traffic Grooming for Optical Networks: Foundations and Techniques co-ordinated by Rudra Duta, Ahmed Kamal, and George Rouskas and published by Springer Science.

[2] E. A. Doumith, and M. Gagnaire. Impact of traffic predictability on WDM EXC/OXC network’s performance. To appear in Procs. of the IEEE Journal on Selected Areas in Communications (JSAC), Issue on traffic engineering for multi-layer networks, pages 895–904, June 2007.

[3] E. A. Doumith, and M. Gagnaire. Traffic routing in a multi-layer optical network considering rerouting and grooming strategies. In Procs. of the 49th IEEE Global Communication Conference (GLOBECOM’06), San Francisco California USA, December 2006.

[4] E. A. Doumith, and M. Gagnaire. Traffic grooming in multi-layer WDM networks: Metaheuristics versus sequential algorithms. In Procs. of the 12th IEEE EUNICE Open European Summer School (EUNICE’06), pages 129–136, Stuttgart Germany, September 2006.

[5] E. A. Doumith, M. Gagnaire, O. Audouin, and R. Douville. From network planning to traffic engineering for optical VPN and multi-granular random demands. In Procs. of the 25th IEEE International Performance Computing and Communication Conference (IPCCC’06), pages 127–134, Phoenix Arizona USA, April 2006.

[6] E. A. Doumith, M. Gagnaire, O. Audouin, and R. Douville. Network nodes dimensioning assuming electrical traffic grooming in an hybrid OXC/EXC WDM network. In Procs. of the 2nd IEEE/Create-Net International Conference on Broadband Networks (BROADNETS’05), pages 286–294, Boston Massachusetts USA, October 2005.

[7] E. A. Doumith, M. Gagnaire, O. Audouin, and N. Puech. Traffic engineering for virtual private networks and random traffic demands in WDM optical core networks. In Procs. of the 14th IEEE International Conference on Computer Communications and Networks (ICCCN’05), pages 317–322, San Diego California USA, October 2005.

[8] E. A. Doumith, M. Koubaa, N. Puech, and M. Gagnaire. Gain and cost brought in by wavelength conversion for the routing and wavelength assignment of two traffic classes in WDM networks. In Procs. of the 10th European Conference on Networks & Optical Communications (NOC’05), pages 147–154, London UK, July 2005.

Table des Matières

Part I Introduction

1 Introduction

1.1 Introduction

1.2 Traffic Grooming

1.3 Reconfiguration Techniques

1.3.1 Logical Topology Reconfiguration

1.3.2 Rerouting

1.4 Motivation

1.5 Thesis Overview

2 Operator’s Network Evolution

2.1 Introduction

2.2 Multi-layer Recovery Approaches

2.2.1 Single-layer Recovery Schemes in Multi-layer Networks

2.2.2 Static Multi-layer Recovery Scheme

2.2.3 Dynamic Multi-layer Recovery Scheme

2.3 Quality of Transmission Aware Networks

2.3.1 Effects of Transmission Impairments on RWA

2.3.2 All-optical Impairment-Aware Routing

2.3.3 Translucent Network Design

Part II Traffic Grooming and Rerouting in Multi-layer WDM Network

3 Backbone Traffic Characterization

3.1 Introduction

3.2 Background

3.3 Data Measurement and Analysis

3.4 Traffic Modeling

3.4.1 Scheduled Demands (SxDs)

3.4.2 Random and semi-Random Demands (RxDs/sRxDs)

3.5 Traffic Metrics

3.6 Traffic Sets

4 Nodal Architecture

4.1 Overview

4.2 Node Architecture

4.2.1 Optical Nodes

4.2.2 Electrical Nodes

4.2.3 Wavelength Converters

4.2.4 Signaling Protocol

4.3 Adopted Node Architecture

4.4 Auxiliary Graph Model

5 Routing and Grooming of Scheduled Demands (SxD)

5.1 Introduction

5.2 Grooming

5.3 Description of the Problem

5.4 Mathematical Formulation

5.4.1 Network Cost Computation in the Case of SLDs

5.4.2 Network Cost Computation in the Case of SEDs

5.4.3 Resource Sharing between SLDs and SEDs

5.4.4 Lower Bound on the Network Cost in the Case of SEDs

5.5 The Linear Programming Approach

5.5.1 Mathematical ILP Formulation of the SLDs’ Routing Problem assuming K-shortest Path Pre-computation

5.5.2 General Mathematical ILP Formulation of the SLDs’ Routing Problem

5.5.3 Mathematical ILP Formulation of the SEDs’ Routing and Grooming Problem assuming K-shortest Path Pre-computation

5.6 The Heuristic Approach

5.6.1 Simulated Annealing Algorithm for SLD and SED Routing

5.6.2 Iterative Greedy Algorithm for SED Grooming

5.7 Simulation Results and Analysis

5.7.1 SLD Routing: ILP vs SA

5.7.2 SLD Routing under Limited Number of Wavelengths per Fiber: ILP vs SA

5.7.3 SED Routing: ILP vs SA

5.7.4 SED Grooming: Various Approaches

5.7.5 Resource Sharing between SLDs and SEDs

5.7.6 Evolution over Time of the Heuristic Approaches

5.7.7 Impact of the SED Routing Solution on the Grooming Procedure

5.7.8 Impact of the Size of the T_list (Parameters: L1 and L2) on the IG Algorithm

5.7.9 Impact of the Number of Iterations (Parameter: N1) on the IG Algorithm

6 Routing and Grooming of Random Demands (sRxD/RxD)

6.1 Network Over-dimensioning

6.2 Traffic Engineering

6.3 Weight Assignment in the Case of sRLDs

6.3.1 Weight Assigned to ‘a’ and ‘d’ edges

6.3.2 Weight Assigned to ‘b’ and ‘e’ edges

6.3.3 Weight Assigned to ‘c’ and ‘f ’ edges

6.3.4 Weight Assigned to ‘g’ and ‘h’ edges

6.3.5 Weight Assigned to ‘o’ edges

6.3.6 Weight Assigned to ‘i’ edges

6.4 Weight Assignment in the Case of sREDs

6.4.1 Weight Assigned to ‘a’ and ‘d’ edges

6.4.2 Weight Assigned to ‘b’ and ‘e’ edges

6.4.3 Weight Assigned to ‘c’ and ‘f ’ edges

6.4.4 Weight Assigned to ‘g’ and ‘h’ edges

6.4.5 Weight Assigned to ‘o’ edges

6.4.6 Weight Assigned to ‘i’ edges

6.5 Weight Assignment in the Case of RLDs

6.6 Weight Assignment in the Case of REDs

6.7 Additional Issues

6.8 Simulation Results and Analysis

6.8.1 Network Dimensioning using the Dijkstra Algorithm

6.8.2 Traffic Engineering using the Dijkstra Algorithm

7 Rerouting Strategies

7.1 Path Adjusting Rerouting (PAR) Algorithm

7.1.1 Traditional Rerouting Algorithm

7.1.2 Extension to the Unidirectional Case

7.1.3 Extension to the Path Adjusting Case

7.1.4 The Resulting Path Adjusting Rerouting (PAR) Algorithm

7.2 Time Limited Resource Reservation (TLRR) Algorithm

7.2.1 Motivation

7.2.2 Principle

7.2.3 Additional Issues

7.3 Simulation Results and Analysis

7.3.1 Performance of the PAR Algorithm

7.3.2 Performance of the TLRR Algorith

8 Conclusions

Part III End Matter

A Grids and Grid Networks

A.1 General Attributes of Grid Networks

A.1.1 Abstraction and Virtualization

A.1.2 Resource Sharing

A.1.3 Programmability and Flexibility

A.1.4 Scalability

A.2 Types of Grids

A.3 A Large-scale Grid Solution for Biological and Physical Cross-Site Simulations

B Network Coding

B.1 Origin of Network Coding

B.2 Two Restricted Problems

B.2.1 Multicast Problem

B.2.2 k-Pairs Communication Problem

B.3 From Information Theory to Network Coding

B.3.1 Information Theory

B.3.2 Steiner Tree Packing

B.3.3 Multicommodity Flow

C Radio Over Fiber Technology

C.1 Advantages of ROF Systems

C.1.1 Low Attenuation Loss

C.1.2 Large Bandwidth

C.1.3 Easy Installation and Maintenance

C.1.4 Reduced Power Consumption

C.2 Application of Radio Over Fiber Technology

C.2.1 Mobile Communications

C.2.2 Mobile Broadband Systems

C.2.3 Wireless Local Area Networks

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