Networking Simulation for Intelligent Transportation Systems ebook

Table of Contents

Cover

Title

Copyright

Preface

1 Simulation of Convergent Networks for Intelligent Transport Systems with VSimRTI

1.1. Introduction

1.2. Fundamentals of cooperative ITS

1.3. Overall simulation framework

1.4. Simulation of cellular networks

1.5. Simulation study

1.6. Conclusion

1.7. Bibliography

2 Near-field Wireless Communications and their Role in Next Generation Transport Infrastructures: an Overview of Modelling Techniques

2.1. Near-field wireless technologies

2.2. Characterization of near-field communications

2.3. Discrete event simulators

2.4. Conclusions

2.5. Bibliography

3 Trace Extraction for Mobility in Civil Aeronautical Communication Networks Simulation

3.1. Traffic regulations

3.2. Mobility for network simulation

3.3. Example of mobility trace extraction

3.4. Toward cooperative trajectories

3.5. Bibliography

4 Air-Ground Data Link Communications in Air Transport

4.1. Introduction

4.2. Continental air-ground data link communications and VDL mode 2

4.3. Oceanic air-ground data link communications and AMS(R)S

4.4. Summary and further work

4.5. Bibliography

5 A Virtual Laboratory as an Assessment Tool for Wireless Technologies in Railway Systems

5.1. Introduction

5.2. ERTMS subsystems and related test beds

5.3. A virtual laboratory based on co-simulation for ERTMS evaluation

5.4. Effective use of the ERTMS–OPNET virtual laboratory

5.5. Conclusion

5.6. Bibliography

6 Emulating a Realistic VANET Channel in Ns-3

6.1. Introduction

6.2. Influence of the channel propagation model on VANET simulation

6.3. A way to realistic channel modeling with ns-2

6.4. Realistic channel modeling with ns-3

6.5. Case studies: emulation of realistic VANET channel models in ns-3

6.6. Conclusion and discussion

6.7. Appendix A: The Abbas et al. Model Implementation

6.8. Bibliography

7 CONVAS: Connected Vehicle Assessment System for Realistic Co-simulation of Traffic and Communications

7.1. Introduction

7.2. Related work

7.3. CONVAS co-simulation platform

7.4. Realistic DSRC channel models

7.5. Channel model tuning

7.6. Connected vehicle applications

7.7. Experimental results

7.8. Conclusions

7.9. Acknowledgments

7.10. Bibliography

8 Highway Road Traffic Modeling for ITS Simulation

8.1. Introduction

8.2. Road traffic models

8.3. Fine-tuned measurement-based model

8.4. Comparative analysis of road traffic models

8.5. Fundamental properties of highway vehicular networks

8.6. Discussion and conclusions

8.7. Bibliography

9 F-ETX: A Metric Designed for Vehicular Networks

9.1. Introduction

9.2. Link quality estimators

9.3. Analysis of legacy estimation techniques

9.4. The F-ETX metric

9.5. Simulation settings

9.6. Simulation results

9.7. Conclusion

9.8. Bibliography

10 Autonomic Computing and VANETs: Simulation of a QoS-based Communication Model

10.1. Introduction

10.2. Autonomic Computing within VANETs

10.3. Broadcasting protocols for VANETs

10.4. Autonomic broadcasting within VANETs

10.5. Simulation of a QoS-based communication model

10.6. Conclusion

10.7. Bibliography

List of Authors

Index

End User License Agreement

List of Tables

1 Simulation of Convergent Networks for Intelligent Transport Systems with VSimRTI

Table 1.1. Simulation parameters for the application modules

Table 1.2. Simulation parameters for the communication properties

2 Near-field Wireless Communications and their Role in Next Generation Transport Infrastructures: an Overview of Modelling Techniques

Table 2.1. Value of λ/2π (cm) for different wavelengths

6 Emulating a Realistic VANET Channel in Ns-3

Table 6.1. IEEE802.11a and p PHY parameters

Table 6.2. Simple Yans WiFi propagation channel model simulation parameters

Table 6.3. Simple Physim WiFi propagation channel model simulation parameters

7 CONVAS: Connected Vehicle Assessment System for Realistic Co-simulation of Traffic and Communications

Table 7.1. Parameter selections for common propagation models

Table 7.2. Parameters for Lognormal-Nakagami model tuned to match urban and residential/suburban scenarios from the SPMD dataset, and [KAR 11] for highway scenarios

Table 7.3. Wireless communication simulation parameters

Table 7.4. Summary of IDZA simulation scenarios and performance

8 Highway Road Traffic Modeling for ITS Simulation

Table 8.1. IDM and MOBIL parameter settings

9 F-ETX: A Metric Designed for Vehicular Networks

Table 9.1. LQE review

Table 9.2. Signal propagation parameter

10 Autonomic Computing and VANETs: Simulation of a QoS-based Communication Model

Table 10.1. Message priority levels

Table 10.2. Topology parameters for different network density levels

Table 10.3. ADM’s parameters and performance results for a high-density network

Table 10.4. ADM’s parameters and performance results for a medium-density network

Table 10.5. ADM’s parameters and performance results for a low-density network

Table 10.6. ADM’s parameters and performance results for a very low-density network

Guide

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Table of Contents

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Series EditorAbdelhamid Mellouk

Networking Simulation for Intelligent Transportation Systems

High Mobile Wireless Nodes

Edited by

First published 2017 in Great Britain and the United States by ISTE Ltd and John Wiley & Sons, Inc.

Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright, Designs and Patents Act 1988, this publication may only be reproduced, stored or transmitted, in any form or by any means, with the prior permission in writing of the publishers, or in the case of reprographic reproduction in accordance with the terms and licenses issued by the CLA. Enquiries concerning reproduction outside these terms should be sent to the publishers at the undermentioned address:

ISTE Ltd27-37 St George’s RoadLondon SW19 4EUUK

www.iste.co.uk

John Wiley & Sons, Inc.111 River StreetHoboken, NJ 07030USA

www.wiley.com

© ISTE Ltd 2017

The rights of Benoit Hilt, Marion Berbineau, Alexey Vinel and Alain Pirovano to be identified as the authors of this work have been asserted by them in accordance with the Copyright, Designs and Patents Act 1988.

Library of Congress Control Number: 2017930998

British Library Cataloguing-in-Publication Data

A CIP record for this book is available from the British Library

ISBN 978-1-84821-853-6

Preface

Nowadays, network simulation has become more affordable than real-world experiments and the least-expensive mean for the evaluation of networking propositions for Intelligent Transportation Systems. This requires that, for purposes of accuracy, simulation software adapts to the simulated field. Which, for the case of ITS, results in integration of realistic mobility, wireless communication environments, and protocol mechanisms that are as precise as possible.

However, every simulation user should be aware of the fact that simulation only represents the functioning of the real world in a limited way.

In this book, we show how simulation can be used in several domains of ITS, ranging from vehicular to railway and aircraft communication networks, with appropriate examples. In the 10 chapters of this book, several levels of the communication models and the technologies of ITS communication are addressed. This ranges from channel modeling to traffic generation, including access layer and routing.

In Chapter 1, Robert Proztmann et al. address the scalability of vehicular communication technologies on the basis of IEEE802.11p when mixed with LTE technology. They present a multi-aspect simulation environment called VSimRTI, a comprehensive framework that connects various simulation tools together to cover all aspects needed for a proper evaluation of new cooperative mobility solutions for ITS.

In Chapter 2, Christian Pinedo et al. address the challenges associated with the interaction of the Internet of Things (IoT) and the ITS domain. They aim to provide guidelines on modeling these smart, low-cost, near-field wireless objects and on how to integrate their behavior in traditional network Discrete Event Simulation (DES) tools.

In Chapter 3, Fabien Garcia et al. analyze the current traffic regulations in different airspaces. They lay out the constraints in aircraft movement as well as the different types of mobility models and their respective merits. They finally present traffic traces’ extraction, enhancement and filtering, leading to new developments on cooperative trajectory studies as a new trend.

In Chapter 4, Christophe Guerber et al. deal with data exchanges between on-board and ground systems. They explain how simulation can be a solution to assess the performances of aeronautical communication architectures and protocols through the examples of communication technologies such as VHF Data Link (VDL) and Aeronautical Mobile-Satellite Service (AMSS).

In Chapter 5, Patrick Sondi et al. propose, in the context of the European Rail Traffic Management System (ERTMS), a virtual laboratory based on co-simulation. It relies on two existing tools: an ERTMS simulator implementing the functional subsystem (ETCS) and an OPNET simulator that enables the modeling of the whole telecommunication subsystem, namely the GSM-R (Global System for Mobile Communications  Railways). They also address the evolution from co-simulation to multi-modeling in order to directly connect the models and avoid the problems related to heterogeneity of simulators.

In Chapter 6, Herve Boeglen et al. show the effects encountered when WiFi frames are transmitted over the air. They provide a channel simulation solution, which is a trade-off between computing time and realism. The source code for ns-3 of this solution is provided in an appendix.

In Chapter 7, Justinian Rosca et al. present a platform that flexibly integrates a traffic simulator with a communication simulator, thus providing an ideal platform for co-simulating transportation system applications. The communication models can be tuned on the basis of real-world measurements in scenarios such as urban, residential and highway traffic.

In Chapter 8, Marco Gramaglia et al. focus on the representation of road traffic for the simulation of highway vehicular networks based on V2V communication technologies and present an original, fine-tuned, measurement-based mobility model.

In Chapter 9, Sebastien Bindel et al. explore the Link Quality Estimators (LQE) in the context of VANET. They propose a metric (F-ETX) that automatically adapts to the link quality and provides a trade-off between the dynamicity and accuracy of Link Quality assessment.

In Chapter 10, Nader Mbarek et al. show how to adapt the Autonomic Computing paradigm to ITS and in particular to Vehicular Ad hoc Networks (VANETs) in order to enhance the performance of communications in such changing environments. The design of a QoS-based broadcasting protocol is presented as a usage case.

We hope that this multi-purpose book will help the reader to move a step forward in their understanding and/or current work in the domain of network simulation for Intelligent Transportation Systems.

Benoit HILT

Marion BERBINEAU

Alexey VINEL

Alain PIROVANO

February 2017