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.

Acronyms and Notations

ACAR Adaptive Connectivity Aware Routing

ACO Ant Colony Optimization

AMR Adaptive Message Routing

AODV Ad hoc on-demand Distance Vector

BLA Bees Life Algorithm

CAN Controller Area Network

CAR Connectivity-Aware Routing

CBRP Cluster-based Routing Protocol

CMGR Connectivity-aware Minimum-delay Geographic Routing

COIN Clustering algorithm for Open Inter-vehicle Networks

DREAM Distance Routing Effect Algorithm for Mobility

DSRC Dedicated Short Range Communications

DYMO Dynamic MANET On-demand

FAST Fuzzy-Assisted Social-based rouTing

GA Genetic Algorithm

GPCR Greedy Perimeter Coordinator Routing

GPS Global Positioning System

GPSR Greedy Perimeter Stateless Routing

HLAR Hybrid Location-based Ad hoc Routing

xvi Bio-inspired Routing Protocols for Vehicular Ad Hoc Networks

HyBR Hybrid Bee swarm Routing

IEEE 1609 Family of Standards for wireless access in vehicular environments (WAVE)

IEEE 802.11 Set of media access control (MAC) and physical layer (PHY) specifications for implementing wireless local area network

IEEE 802.11a An amendment to the IEEE 802.11 defining requirements for an orthogonal frequency division multiplexing (OFDM) communication system

IEEE 802.11p An amendment to the IEEE 802.11 to add wireless access in vehicular environments

IGRP Intersection-based Geographical Routing Protocol

IP Internet Protocol

ISO International Organization for Standardization

ITS Intelligent Transportation System

IVC Inter-Vehicle Communication

LIN Local Interconnect Network

LocVSDP Location-based Vehicular Service Discovery Protocol

LTE Long Term Evolution

MAC Medium Access Control

MANET Mobile Ad hoc NETwork

MAR-DYMO Mobility-aware Ant colony optimization Routing DYMO

MAV-AODV Multicast with Ant Colony Optimization for VANET

MURU MUlti-hop Routing protocol for Urban

ns-2 Network Simulator

OBU On-Board Unit

OFDM Orthogonal Frequency Division Multiplexing

OLSR Optimized Link State Routing

PassCAR Passive Clustering Aided Routing

Acronyms and Notations xvii

PBR Prediction Based Routing

PLCP Physical Layer Convergence Procedure

PMD Physical Medium Dependent

PSO Particle Swarm Optimization

QoS Quality of Service

QoSBeeVANET Quality of Service Bee Swarm routing protocol for VANET

RBVT-P Road-Based using Vehicular Traffic Proactive

RIVER Reliable Inter-VEhicular Routing

ROMSGP Receive on Most Stable Group-Path

RSU Roadside Unit

SLAB Statistical Location-Assisted Broadcast

SUMO Simulation of Urban MObility

TACR Trust dependent Ant Colony Routing

VADD Vehicle-Assisted Data Delivery

VANET Vehicular Ad hoc NETwork

VCN Vehicular Cellular Network

VRC Vehicle-to-Roadside Communication

V-WLAN Vehicular Wireless Local Area Network

WAVE Wireless Access in Vehicular Environment

Wi-Fi Wireless Fidelity

WiMAX Worldwide Interoperability for Microwave Access

WSM WAVE Short Message

WSMP WAVE Short Message Protocol