Traffic Engineering and QoS Optimization of Integrated Voice & Data Networks

Front Cover

Title Page

Copyright Page

Table of Contents

Foreword

Preface

Acknowledgments

About the Author

Chapter 1 Traffic Engineering and QoS Optimization Models

1.1 Introduction

1.2 Terminology and Definitions

1.3 TQO Background and Motivation

1.4 TQO Functional Model

1.4.1 Traffic/Application Layer

1.4.2 MPLS LSPs/Layer 3

1.4.3 Logical Links/GMPLS LSPs/Layer 2

1.4.4 Physical Fiber Transport/Layer 1

1.4.5 Operational/Management Layer

1.5 TQO Design

1.5.1 TQO Design Problem Statement

1.5.1.1 Traffic/Application Layer Design

1.5.1.2 MPLS LSP Dynamic Routing and Bandwidth Allocation Layer 3 Design

1.5.1.3 GMPLS LSP (Logical Link) Routing and Bandwidth Allocation Layer 2 Design

1.5.1.4 Physical Fiber Transport/Layer 1 Design

1.5.1.5 Operational/Management Layer Design

1.5.2 TQO Design Approach

1.5.2.1 Design and Operational Experience

1.5.2.2 Modeling, Analysis, and Case Studies

1.6 TQO Design and Operational Experience

1.6.1 Design and Operational Experience in Data Networks

1.6.1.1 Data Network Routing Layer Design/Operational Experience

1.6.1.2 Data Network Management Layer Design/Operational Experience

1.6.2 Design and Operational Experience in Voice Networks

1.6.2.1 Voice Network Routing Layer Design/Operational Experience

1.6.2.2 Voice Network Management Layer Design/Operational Experience

1.6.2.3 Benefits Derived from TQO Design/Operational Experience in Voice Networks

1.6.3 TQO Design Principles and Benefits Derived from Experience

1.7 Modeling, Analysis, and Case Studies

1.7.1 Analysis, Design, and Optimization Methods Used in Modeling Studies

1.7.1.1 Routing Design and Optimization Methods

1.7.1.2 Capacity Design and Optimization Methods

1.7.1.3 QoS and GoS Performance Measures

1.7.2 Key Results from Modeling Studies

1.8 Generic TQO (GTQO) Protocol and Benefits

1.9 Standards Needs to Realize GTQO Protocol Requirements

1.10 Conclusion and Applicability of Requirements

Chapter 2 Call/Session Routing and Connection Routing Methods

2.1 Introduction

2.2 Call/Session Routing Methods

2.3 Connection (Bearer-Path) Routing Methods

2.3.1 Hierarchical Fixed Routing Path Selection

2.3.2 Time-Dependent Routing Path Selection

2.3.3 State-Dependent Routing Path Selection

2.3.4 Event-Dependent Routing Path Selection

2.4 Internetwork Routing

2.5 Modeling of TQO Methods

2.5.1 Network Design Comparisons

2.5.2 Network Performance Comparisons

2.5.3 Single-Area Flat Topology vs Multiarea Two-Level Hierarchical Network Topology

2.5.4 Network Modeling Conclusions

2.6 Summary and Conclusions

2.7 Applicability of Requirements

Chapter 3 Traffic Engineering and QoS Optimization of MPLS-Based Integrated Voice/Data Dynamic Routing Networks

3.1 Introduction

3.2 Class-of-Service Routing

3.2.1 Class-of-Service Identification

3.2.2 Routing Table Derivation

3.2.3 Class-of-Service Routing Steps

3.3 Dynamic Bandwidth Allocation, Protection, and Reservation Principles

3.3.1 Per-VNET Bandwidth Allocation, Protection, and Reservation

3.3.1.1 Per-VNET Bandwidth Allocation/Reservation: Meshed Network Case

3.3.1.2 Per-VNET Bandwidth Allocation/Reservation: Sparse Network Case

3.3.2 Per-Flow Bandwidth Allocation, Protection, and Reservation

3.3.2.1 Per-Flow Bandwidth Allocation/Reservation: Meshed Network Case

3.3.2.2 Per-Flow Bandwidth Allocation/Reservation: Sparse Network Case

3.4 Queuing Mechanisms

3.5 Internetwork QoS Resource Management

3.6 Modeling of TQO Methods

3.6.1 Performance of Bandwidth Reservation Methods

3.6.2 Per-VNET vs Per-Flow Bandwidth Allocation

3.6.3 Single-Area Flat Topology vs Multiarea Two-Level Hierarchical Flat Topology

3.6.4 Need for MPLS and DiffServ

3.7 Summary and Conclusions

3.8 Applicability of Requirements

Chapter 4 Routing Table Management Methods and Requirements

4.1 Introduction

4.2 Routing Table Management for IP-Based Networks

4.3 Routing Table Management for ATM-Based Networks

4.4 Routing Table Management for TDM-Based Networks

4.5 Signaling and Information Exchange Requirements

4.5.1 Call/Session Routing (Number Translation to Routing Address) Information-Exchange Parameters

4.5.2 Connection Routing Information-Exchange Parameters

4.5.3 QoS Resource Management Information-Exchange Parameters

4.5.4 Routing Table Management Information-Exchange Parameters

4.5.5 Harmonization of Information-Exchange Standards

4.5.6 Open Application Programming Interface (API)

4.6 Examples of Call/Session Setups

4.6.1 Time-Dependent Routing Call/Session Setup

4.6.2 Distributed Connection-by-Connection State-Dependent Routing (DC-SDR) Call/Session Setup

4.6.3 Centralized Periodic State-Dependent Routing (CP-SDR) Call/Session Setup

4.6.4 Event-Dependent Routing Call/Session Setup

4.7 Examples of Internetwork Routing

4.7.1 Internetwork E Uses a Mixed Path Selection Method

4.7.2 Internetwork E Uses a Single Path Selection Method

4.8 Modeling of TQO Methods

4.9 Summary and Conclusions

4.10 Applicability of Requirements

Chapter 5 Traffic Engineering and QoS Optimization of GMPLS-Based Multilayer Dynamic Routing Networks

5.1 Introduction

5.2 GMPLS-Based Dynamic Transport Routing Principles

5.3 GMPLS-Based Dynamic Transport Routing Examples

5.3.1 Seasonal Traffic Variations Example

5.3.2 Week-to-Week Traffic Variations Example

5.3.3 Daily Traffic Variations Example

5.3.4 Real-Time Traffic Variations Example

5.4 Distributed Real-Time Dynamic Transport Routing Algorithm Design

5.4.1 Estimate Traffic

5.4.2 Size Layer 3 MPLS LSP VNET Capacity

5.4.3 Reallocate Access Capacity between Overloaded and Underloaded Traffic Routers

5.4.4 Compute Diverse Capacity

5.4.5 Size Layer 2 ALL and BLL Capacity

5.4.6 Reroute ALL and BLL Capacity

5.5 Reliable Transport Network Design

5.5.1 Transport Link Design Models

5.5.2 Node Design Models

5.6 Modeling of TQO Methods

5.6.1 GMPLS-Based Dynamic Transport Routing Capacity Design

5.6.2 Performance for Network Failures

5.6.3 Performance for General Traffic Overloads

5.6.4 Performance for Unexpected Overloads

5.6.5 Performance for Peak-Day Traffic Loads

5.7 Summary and Conclusions

5.8 Applicability of Requirements

Chapter 6 Optimization Methods for Routing Design and Capacity Management

6.1 Introduction

6.2 Routing Design and Optimization Methods

6.2.1 Discrete Event Simulation Models

6.2.2 Shortest Path Routing Design Models

6.2.3 Hierarchical Routing Design Models

6.3 Capacity Design and Optimization Methods

6.3.1 Capacity Design Cost Impacts for Traffic Load Variations

6.3.1.1 Impacts of Within-the-Hour Minute-to-Minute Traffic Variations

6.3.1.2 Impacts of Hour-to-Hour Traffic Variations

6.3.1.3 Impacts of Day-to-Day Traffic Variations

6.3.1.4 Impacts of Week-to-Week Traffic Variations

6.3.2 Capacity Design and Optimization Models

6.3.2.1 Discrete Event Flow Optimization Models

6.3.2.2 Discussion of DEFO Model

6.3.2.3 Example Application of DEFO Model

6.3.2.4 Traffic Load Flow Optimization Models

6.3.2.5 Link Flow Optimization Model

6.3.2.6 Virtual Trunk Flow Optimization Models

6.3.2.7 Dynamic Transport Routing Capacity Design Models

6.4 Modeling of TQO Methods

6.4.1 Per-VNET vs Per-Flow Network Design

6.4.2 Integrated vs Separate Voice/ISDN and Data Network Designs

6.4.3 Multilink vs Two-Link Network Design

6.4.4 Single-Area Flat vs Two-Level Hierarchical Network Design

6.4.5 EDR vs SDR Network Design

6.4.6 Dynamic Transport Routing vs Fixed Transport Routing Network Design

6.5 Summary and Conclusions

6.6 Applicability of Requirements

Chapter 7 Traffic Engineering and QoS Optimization Operational Requirements

7.1 Introduction

7.2 Traffic Management

7.2.1 Real-Time Performance Monitoring

7.2.2 Network Control

7.2.3 Work Center Functions

7.2.3.1 Automatic Controls

7.2.3.2 Code Controls

7.2.3.3 Reroute Controls

7.2.3.4 Peak-Day Control

7.2.4 Traffic Management on Peak Days

7.2.5 Interfaces to Other Work Centers

7.3 Capacity Management: Forecasting

7.3.1 Load Forecasting

7.3.1.1 Configuration Database Functions

7.3.1.2 Load Aggregation, Basing, and Projection Functions

7.3.1.3 Load Adjustment Cycle and View of Business Adjustment Cycle

7.3.2 Network Design

7.3.3 Work Center Functions

7.3.4 Interfaces to Other Work Centers

7.4 Capacity Management: Daily and Weekly Performance Monitoring

7.4.1 Daily Congestion Analysis Functions

7.4.2 Study-Week Congestion Analysis Functions

7.4.3 Study-Period Congestion Analysis Functions

7.5 Capacity Management: Short-Term Network Adjustment

7.5.1 Network Design Functions

7.5.2 Work Center Functions

7.5.3 Interfaces to Other Work Centers

7.6 Comparison of Off-Line (FXR/TDR) versus On-Line (SDR/EDR) TQO Methods

7.7 MPLS Operations Architecture Example

7.7.1 Connectivity to Managed Assets

7.7.2 Modeling of VPN Topologies

7.7.3 Fault Management

7.7.4 Performance Management

7.7.5 MPLS MIB Architecture

7.7.6 MPLS OAM Operational Experience

7.8 Summary and Conclusions

7.9 Applicability of Requirements

Chapter 8 Case Studies 1: Traffic Engineering and QoS Optimization for Operational Integrated Voice/Data Dynamic Routing Networks

8.1 Introduction

8.2 Case Study: TQO Protocol Design of Circuit-Switched Integrated Voice/Data Dynamic Routing Network

8.2.1 Principles of TQO Protocol Design for Integrated Voice/Data Dynamic Routing Networks

8.2.1.1 Class-of-Service Routing

8.2.1.2 Connection Admission Control (CAC), Source-Based Path Selection, Crankback

8.2.1.3 Load State Mapping, Bandwidth Reservation

8.2.1.4 Dynamic Connection Routing, Priority Routing

8.2.1.5 Meet Performance Objectives for Integrated COSs

8.2.2 Optimization of TQO Protocol

8.3 Case Study: TQO Protocol Design of Circuit-Switched, Internetwork, Integrated Voice/Data Dynamic Routing Networks

8.4 Case Studies: Examples of Alternate Routing Contributing to Network Congestion

8.5 Applicability of Requirements

Chapter 9 Case Studies 2: Traffic Engineering and QoS Optimization for Operational Integrated Voice/Data Dynamic Routing Networks

9.1 Introduction

9.2 Case Study: TQO Protocol Design of MPLS/GMPLS-Based IntegratedVoice/Data Dynamic Routing Network

9.3 Optimization of TQO Path Selection Protocol

9.4 Optimization of TQO Bandwidth Management Protocol

9.4.1 TQO Bandwidth Management Protocol Options

9.4.1.1 Option A (Direct Coordination): MSE CAC, DSTE/MAR, DiffServ/Five Queues

9.4.1.2 Option B (Indirect Coordination): GW CAC, DSTE/MAM, DiffServ/Five Queues

9.4.1.3 Option C (Indirect Coordination): GW CAC, No DSTE, DiffServ/Three Queues

9.4.1.4 Option D (No Coordination): No CAC, No DSTE, DiffServ/Three Queues

9.4.1.5 Option E (No Coordination): No CAC, No DSTE, No DiffServ/One Queue

9.4.2 Traffic, Network Design, and Simulation Model Description

9.4.2.1 Traffic Model Description

9.4.2.2 Network Design Model Description

9.4.2.3 Simulation Model Description

9.5 Modeling Results

9.6 Summary and Conclusions

9.7 Applicability of Requirements

Chapter 10 Summary, Conclusions, and Generic Traffic Engineering and QoS Optimization Requirements

10.1 Introduction

10.2 TQO Modeling and Analysis

10.3 Summary and Conclusions Reached

10.3.1 Chapter 1: Summary and Conclusions on TQO Models

10.3.2 Chapter 2: Summary and Conclusions on Call/Session Routing and Connections Routing Methods

10.3.3 Chapter 3: Summary and Conclusions on TQO Protocol Design for MPLS-Based Dynamic Routing Networks

10.3.4 Chapter 4: Summary and Conclusions on Routing Table Management Methods and Requirements

10.3.5 Chapter 5: Summary and Conclusions on TQO Protocol Design of GMPLS-Based Multilayer Dynamic Routing Networks

10.3.6 Chapter 6: Summary and Conclusions on Optimization Methods for Routing Design and Capacity Management

10.3.7 Chapter 7: Summary and Conclusions on TQO Operational Requirements

10.3.8 Chapters 8 and 9: Summary and Conclusions on Case Studies of TQO for Operational Integrated Voice/Data Dynamic Routing Networks

10.4 GTQO Protocol for MPLS/GMPLS-Based Integrated Voice/Data Dynamic Routing Networks

10.4.1 GTQO Protocol Requirements

10.4.2 GTQO Capabilities to Meet Requirements

10.4.3 GTQO Protocol Description

10.5 Comparative Analysis of GTQO Protocol Model and Alternative Models

10.5.1 Distributed TQO Approaches

10.5.1.1 Distributed VNET-Based TQO Approaches with CAC

10.5.1.2 Flow-Aware Networking (Distributed TQO Approach without CAC)

10.5.2 Centralized TQO Approaches

10.5.2.1 TQO Processor (TQOP)

10.5.2.2 Resource and Admission Control Function (RACF)

10.5.2.3 Intelligent Routing Service Control Point (IRSCP)

10.5.2.4 DiffServ Bandwidth Broker

10.5.2.5 Network-Aware Resource Broker (NARB)

10.5.3 Competitive and Cooperative Game Theoretic Models

10.6 Needed Standards Extensions and Technologies to Meet GTQO Protocol Requirements

10.6.1 DiffServ-Aware MPLS Traffic Engineering (DSTE)

10.6.2 Path Computation Element (PCE)

10.6.3 RSVP Aggregation Extensions over DSTE Tunnels

10.6.4 Header Compression over MPLS

10.6.5 QoS Signaling Protocol

10.6.6 Crankback Routing for MPLS LSP Setup or Modification

10.6.7 OSPF Congestion Control

10.6.8 PseudoWire

10.6.9 Session Initiation Protocol (SIP)

10.6.10 IP Multimedia Subsystem (IMS)

10.6.11 Broadband Remote Access Server (BRAS)

10.6.12 Dynamic Quality of Service (DQOS)

10.6.13 Session Border Controller (SBC)

10.7 Benefits of GTQO Protocol for MPLS/GMPLS-Based Dynamic Routing Networks

10.8 Applicability of Requirements

Appendix A Traffic Engineering and QoS Optimization Technology Overview

A.1 Introduction

A.2 Multiprotocol Label Switching (MPLS)

A.3 Generalized Multiprotocol Label Switching (GMPLS)

A.4 QoS Mechanisms

A.4.1 Traffic Shaping and Policing Algorithms

A.4.1.1 Leaky-Bucket Algorithm

A.4.1.2 Token-Bucket Algorithm

A.4.2 Queue Management and Scheduling

A.5 Integrated Services (IntServ)

A.6 Resource Reservation Protocol (RSVP)

A.7 Differentiated Services (DiffServ)

A.8 MPLS-Based QoS Mechanisms

Glossary

References and Bibliography

Index