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Vehicular Ad-Hoc Networks (VANETs) play a key role in developing IntelligentTransportation Systems (ITS) aiming to achieve road safety and to guarantee theneeds of drivers and passengers, in addition to improving transportation productivity.

One of the most important challenges of this kind of network is the data routingbetween VANET nodes which should be routed with a high level of Quality of Service(QoS) to ensure messages are received in time. The driver can then make theappropriate decision to improve road safety. In the literature, there are several routingprotocols for VANETs which are of varying reliability in reaching safety requirements.

In this book, the authors begin by describing all the basic concepts of VANETs, suchas VANET definition, VANET versus Mobile Ad-hoc Network (MANET), architectures,routing definition and steps, Quality of Service (QoS) for VANET routing, metrics ofevaluation, experimentation, and simulation of VANETs, mobility patterns of VANETs,etc. Moreover, different routing protocols for routing in VANETs are described. Twomain categories are presented: classical routing and bio-inspired routing. Concerningclassical VANETs, the main principles and all phases are overviewed, as well as theirtwo sub-categories which are topological and geographical protocols.

0Following this, the authors propose a new category called bio-inspired routing whichis inspired by natural phenomena such as ant colony, bee life, genetic operators, etc.They also present some referential protocols as examples of each category.

Salim Bitam is Associate Professor and responsible for the Master in DecisionSupport Systems and Multimedia in the computer science department at theUniversity of Biskra, Algeria, as well as a Senior Member of LESIA Laboratory(University of Biskra, Algeria), and Associate Member of LiSSi Laboratory (Universityof Paris-Est Créteil VdM, France). His main research interests are vehicular ad-hocnetworks, mobile ad-hoc networks, wireless sensor networks, cloud computing, andbio-inspired methods for routing and optimization.

Abdelhamid Mellouk is Full Professor at the University of Paris-Est (UPEC),Networks & Telecommunications (N&T) Department and LiSSi Laboratory, France.Head of several executive national or international positions, he is the founder of theNetwork Control Research activity in UPEC with extensive international academicand industrial collaborations. His general area of research is in adaptive real-timecontrol for high-speed new generation dynamic wired/wireless networking in order tomaintain acceptable Quality of Service/Experience for added value services.

Bio-inspired RoutingProtocols for Vehicular

Ad-Hoc Networks

FOCUS

Salim BitamAbdelhamid Mellouk

NETWORKS AND TELECOMMUNICATIONS SERIES

FOCUS SERIES in NETWORKS AND TELECOMMUNICATIONS

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Bio-inspired Routing Protocols for Vehicular Ad Hoc Networks

FOCUS SERIES

Series Editor Abdelhamid Mellouk

Bio-inspired Routing Protocols for Vehicular

Ad Hoc Networks

Salim Bitam Abdelhamid Mellouk

First published 2014in 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 Ltd John Wiley & Sons, Inc. 27-37 St George’s Road 111 River Street London SW19 4EU Hoboken, NJ 07030 UK USA

www.iste.co.uk www.wiley.com

© ISTE Ltd 2014 The rights of Salim Bitam and Abdelhamid Mellouk 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: 2014945528 British Library Cataloguing-in-Publication Data A CIP record for this book is available from the British Library ISSN 2051-2481 (Print) ISSN 2051-249X (Online) ISBN 978-1-84821-663-1

Contents

PREFACE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix

INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xi

ACRONYMS AND NOTATIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xv

CHAPTER 1. VEHICULAR AD HOC NETWORKS . . . . . . . . . . . . . . . . . . . 1

1.1. VANET definition, characteristics and applications . . . . . . . . . . . . . 1 1.1.1. Definition of vehicular ad hoc network . . . . . . . . . . . . . . . . . 1 1.1.2. Characteristics of vehicular ad hoc networks . . . . . . . . . . . . . 2 1.1.3. Applications of vehicular ad hoc networks . . . . . . . . . . . . . . . 5

1.2. VANET architectures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 1.2.1. Vehicular WLAN/cellular architecture . . . . . . . . . . . . . . . . . 7 1.2.2. Pure ad hoc architecture . . . . . . . . . . . . . . . . . . . . . . . . . . 8 1.2.3. Hybrid architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

1.3. Mobility models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 1.3.1. Random-based mobility models . . . . . . . . . . . . . . . . . . . . . 10 1.3.2. Geographic map-based mobility models . . . . . . . . . . . . . . . . 12 1.3.3. Group-based mobility . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 1.3.4. Prediction-based mobility models . . . . . . . . . . . . . . . . . . . . 17 1.3.5. Software-tools-based mobility models . . . . . . . . . . . . . . . . . 20

1.4. VANET challenges and issues . . . . . . . . . . . . . . . . . . . . . . . . 21 1.4.1. VANET routing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 1.4.2. Vehicular network scalability . . . . . . . . . . . . . . . . . . . . . . . 22 1.4.3. Computational complexity in VANET networking . . . . . . . . . . 22

vi Bio-inspired Routing Protocols for Vehicular Ad Hoc Networks

1.4.4. Routing robustness and self-organization in vehicular networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 1.4.5. Vehicular network security . . . . . . . . . . . . . . . . . . . . . . . . 23

1.5. Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

CHAPTER 2. ROUTING FOR VEHICULAR AD HOC NETWORKS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

2.1. Basic concepts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 2.1.1. Single-hop versus multi-hop beaconing in VANETs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 2.1.2. Routing classification of VANETs . . . . . . . . . . . . . . . . . . . . 31

2.2. Quality-of-service of VANET routing . . . . . . . . . . . . . . . . . . . . 35 2.2.1. Quality-of-service definition . . . . . . . . . . . . . . . . . . . . . . . 35 2.2.2. Quality-of-service criteria . . . . . . . . . . . . . . . . . . . . . . . . . 36

2.3. VANET routing standards . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 2.3.1. Dedicated short range communication . . . . . . . . . . . . . . . . . 38 2.3.2. Standards for wireless access in vehicular environments (WAVE) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 2.3.3. VANET standards related to routing layers . . . . . . . . . . . . . . 42 2.3.4. Other VANET routing standards . . . . . . . . . . . . . . . . . . . . . 44

2.4. VANET routing challenges and issues . . . . . . . . . . . . . . . . . . . . 45 2.4.1. Dynamics nature of VANETs (mobility pattern and vehicles’ velocity) . . . . . . . . . . . . . . . . . . . . 45 2.4.2. Vehicular network density and scalability . . . . . . . . . . . . . . . 46 2.4.3. Safety improvement and quality-of-service . . . . . . . . . . . . . . 46

2.5. Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47

CHAPTER 3. CONVENTIONAL ROUTING PROTOCOLS FOR VANETS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51

3.1. Topology-based routing . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 3.1.1. Reactive routing protocols . . . . . . . . . . . . . . . . . . . . . . . . 52 3.1.2. Proactive routing protocols . . . . . . . . . . . . . . . . . . . . . . . . 55 3.1.3. Hybrid routing protocols . . . . . . . . . . . . . . . . . . . . . . . . . 57 3.1.4. Critics of topology-based routing . . . . . . . . . . . . . . . . . . . . 58

3.2. Geography-based routing . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 3.2.1. Geography-based routing principle . . . . . . . . . . . . . . . . . . . 59 3.2.2. Geography-based routing protocols . . . . . . . . . . . . . . . . . . . 59 3.2.3. Critics of geography-based routing . . . . . . . . . . . . . . . . . . . 67

3.3. Cluster-based routing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 3.3.1. Cluster-based routing principle . . . . . . . . . . . . . . . . . . . . . . 68

Contents vii

3.3.2. Cluster-based routing protocols . . . . . . . . . . . . . . . . . . . . . 69 3.3.3. Critics of cluster-based routing . . . . . . . . . . . . . . . . . . . . . . 73

3.4. Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73

CHAPTER 4. BIO-INSPIRED ROUTING PROTOCOLS FOR VANETS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79

4.1. Motivations for using bio-inspired approaches in VANET routing . . . . . . . . . . . . . . . . . . . . . . . . . . . 80

4.1.1. Network scalability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 4.1.2. Computational complexity . . . . . . . . . . . . . . . . . . . . . . . . 80 4.1.3. Self-organization and adaptability . . . . . . . . . . . . . . . . . . . . 81 4.1.4. Routing robustness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81

4.2. Fundamental concepts and operations of bio-inspired VANET routing . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82

4.2.1. Optimization problem definition . . . . . . . . . . . . . . . . . . . . . 82 4.2.2. Search space (SSp) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 4.2.3. Objective function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 4.2.4. Population . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84 4.2.5. Individual encoding . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84 4.2.6. Initialization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84 4.2.7. Stopping criterion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85

4.3. Basic bio-inspired algorithms used in VANET routing literature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85

4.3.1. Genetic algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86 4.3.2. Ant colony optimization . . . . . . . . . . . . . . . . . . . . . . . . . . 89 4.3.3. Particle swarm optimization . . . . . . . . . . . . . . . . . . . . . . . 90 4.3.4. Bees life algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92 4.3.5. Bacterial foraging optimization . . . . . . . . . . . . . . . . . . . . . . 93

4.4. Evolutionary algorithms for VANET routing . . . . . . . . . . . . . . . . 95 4.4.1. Sequential genetic algorithms for VANET routing . . . . . . . . . . 95 4.4.2. Parallel genetic algorithms for VANET routing . . . . . . . . . . . . 100

4.5. Swarm intelligence for VANET routing . . . . . . . . . . . . . . . . . . . 101 4.5.1. Ant colony optimization for VANET routing . . . . . . . . . . . . . 102 4.5.2. Particle swarm optimization for VANET routing . . . . . . . . . . . 106 4.5.3. Bee colony optimization for VANET routing . . . . . . . . . . . . . 108 4.5.4. Bacterial foraging optimization for VANET routing . . . . . . . . . 110

4.6. Another bio-inspired approach for VANET routing . . . . . . . . . . . . 112 4.7. Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113

CONCLUSION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121

INDEX . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125

Preface

It will be fascinating to look back in the years ahead and note the growing interest of bio-inspired computing, short for biologically inspired computing, that has been deployed to solve various computational problems in several disciplines such as networks and telecommunications, imagery, artificial intelligence and decision support systems.

Due to the emergence of different kinds of communication and networking technologies and the foreseen proliferation of different and specific types of services supported by these technologies, the use of bio-inspired techniques seems to be a real challenge, taking into account all the computational complexities.

However, the use of artificial intelligence tools together with biologically inspired techniques is needed to control network behavior in real-time so as to provide users with the quality of service that they request.

The book focuses on the use of these techniques in intelligent transportation systems (ITSs). The latter is considered as one of the most recently studied domains where bio-inspired approaches are successfully applied. ITS design and development play a major role in improving road safety, traffic monitoring and passengers’ comfort in order to avoid accidents and traffic congestion on the one hand, and to serve and satisfy digital needs of vehicle drivers and passengers on the other. To achieve these goals, ITSs need to support traffic information delivery, accurately and timely, to vehicle drivers and transport authorities. This transmission is ensured through a reliable vehicular wireless and mobile network known as a Vehicular Ad hoc NETwork (VANET).

Over the years, the continuous technological evolution and the development of new applications and services have steered networking research toward new problems, which have emerged as the network evolves with new features toward

x Bio-inspired Routing Protocols for Vehicular Ad Hoc Networks

what is usually referred to as the next generation networks, which has become one of the basic infrastructures that supports the world economy nowadays.

This book focuses on the current state-of-the-art research results and experience reports in the area of bio-inspired techniques dedicated to ITSs. It shows that the bio-inspired field is a very dynamic area in terms of theory and application.

To give a complete bibliography and a historical account of the research that led to the present form of the subject would have been impossible. Thus, it is inevitable that some topics have been treated in less detail than others. The choices made reflect, in part, personal taste and expertise and, in part, a preference for very promising research and recent developments in the field of ITS-based bio-inspired techniques.

This book is a start, but also leaves many questions unanswered. I hope that it will inspire a new generation of investigators and investigations.

The authors hope that you will enjoy reading this book and receive many helpful ideas and revelations for your own study.

Abdelhamid MELLOUK July 2014

Introduction

Over the last decade, we have witnessed the emergence of bio-inspired computing, short for biologically inspired computing, that has been deployed to solve various computational problems in several disciplines such as networks and telecommunications, imagery, artificial intelligence and decision support systems.

A bio-inspired technique is defined as a field of study of natural behaviors and biological species aiming to propose new solutions to computational problems such as modeling, optimization and simulation. The basic principle used by these approaches is the imitation of natural behaviors of living creatures such as humans, insects and animals when they try to find solutions to their natural needs such as food or nest searching, reproduction, defense and traveling. The Intelligent Transportation System (ITS) is considered as one of the most recently studied domains where bio-inspired approaches are successfully applied and have given better results compared to conventional approaches which are not biologically inspired.

ITS’s design and development play a major role in improving road safety, traffic monitoring and passengers’ comfort in order to avoid accidents and traffic congestion on one side, and to serve and satisfy digital needs of vehicle drivers and passengers. To achieve these goals, ITSs need to support traffic information delivery accurately and timely to vehicle drivers and transport authorities. This transmission is ensured through a reliable vehicular wireless and mobile network known as a Vehicular Ad hoc NETwork (VANET).

VANET is considered as a specific kind of Mobile Ad hoc NETwork (MANET) which consists of a set of mobile nodes (vehicles) and fixed nodes known as roadside units (RSUs). A VANET provides digital data communication between vehicles through inter-vehicle communication (IVC), and between vehicles and RSUs through vehicle-to-roadside communication (VRC). Due to their restricted

xii Bio-inspired Routing Protocols for Vehicular Ad Hoc Networks

range of motion in terms of directions and speeds, VANET vehicles move according to an organized and restricted mobility model with some distinctions between highways, urban or rural areas. Moreover, a vehicle is equipped with some sort of radio interface called on-board unit (OBU) that enables short-range wireless IVCs and/or VRCs along with a Global Positioning System (GPS) integrated into vehicles to facilitate location-based services.

VANETs can support different types of services such as vehicle safety, automated toll payment, traffic management, enhanced navigation, location-based services (e.g. finding the closest fuel station, restaurant or hotel) and infotainment applications, such as Internet-based services.

This book studies different bio-inspired approaches proposed up to the present which are applied to routing problems for VANETs. The main motivation behind the deployment of bio-inspired techniques for VANET routing arises from the strong similarity between communication scenarios in data packet routing and the natural communication of species. Network scalability is another reason to apply bio-inspired routing against traditional routing which is less efficient for dense VANETs. Moreover, these approaches have proved their effectiveness in solving such problems with high adaptability and robustness in terms of accuracy of results compared to other VANET routing schemes. In fact, the accurate forwarding of data packets is very crucial and important in vehicular networks, since delivering data to its destination in time can help vehicle drivers to react in opportune time, therefore, undesirable situations are avoided and road safety is improved.

This book is divided into five chapters. Chapter 1 contains an introduction and includes bio-inspiration’s purpose, motivations and an overview of the book. Chapter 2 reviews a background of VANETs including definition, characteristics and applications. Also, Chapter 2 presents different VANET architectures and their mobility models, which is concluded by the essential challenges and issues of VANETs.

Chapter 3 is devoted to VANET routing concepts and mechanisms. To achieve this, Chapter 3 highlights basic transmission processes and proposes a classification of proposed routing protocols for VANETs into three categories: topology-based routing, geography-based routing and cluster-based routing. Quality of Service and VANET routing standards are also outlined; then, major issues and challenges facing VANET routing are presented.

The fourth chapter deals with details of conventional routing protocols conceived for VANETs. For each category (i.e. topology-based, geography-based and cluster-based routing) the main principles as well as advantages and weaknesses are

Introduction xiii

explained. In addition, the main protocol of each category is illustrated in detail by schemes and examples.

Chapter 5 provides a detailed knowledge concerning biologically inspired approaches applied for vehicular Ad hoc networks. It starts with motivations for using such methods in VANET routing and describes different basic concepts and operations used by bio-inspired protocols in this context. Afterward, basic bio-inspired algorithms used in VANET routing literature are explained in depth. This part concerns genetic algorithm, ant colony optimization, particle swarm optimization, bee colony optimization and bacterial foraging optimization. Some examples in the VANET area and illustrative schemes are depicted. Moreover, this chapter surveys bio-inspired protocols for VANET routing classified into three categories, namely evolutionary algorithms, swarm intelligence and another bio-inspired source. For each category, a state of the art including proposed protocols, their main principles and discussions are presented.

Finally, this book is concluded with some rough opportunities and future tends of bio-inspired methods for routing in VANETs.