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Large-Scale Simulation of Vehicular Ad Hoc Networks Ricardo Jorge Fernandes Large-scale Simulation of Vehicular Ad Hoc Networks MAP-Tele Doctoral Programme in Telecommunications University of Porto, Minho and Aveiro May, 2014 Ricardo Jorge Fernandes Large-scale Simulation of Vehicular Ad Hoc Networks Disserta¸c~aosubmetida `aFaculdade de Ci^enciasda Universidade do Porto como parte dos requisitos para a obten¸c~aodo grau de Doutor em Telecomunica¸c~oes Orientador: Prof. Michel Ferreira MAP-Tele Doctoral Programme in Telecommunications University of Porto, Minho and Aveiro May, 2014 To my Family and Friends Acknowledgments First of all, I would like to give great thanks to Prof. Michel Ferreira for his availability, scientific advice and for permitting me to turn four years of research into the highest academic diploma. I am also very grateful to Dr. Fausto Vieira for his invaluable advice and many insightful discussions and suggestions. No doubt his commitment and help had a big impact on the resulting work presented here. I am also willing to express my gratitude to Hugo Concei¸c~ao,Pedro D'orey, Pedro Gomes, and Lu´ıs Matias for their contribution on the resulting work presented in here. I am willing to thank to the Portuguese Foundation for Science and Technology (FCT) which permitted me to get into research by providing me a PhD doctoral grant (SFRH/BD/61676/2009) as well as to Instituto de Telecomunica¸c~oesand the Faculty of Sciences of University of Porto for providing me great environment and research facilities. I would also like to express my gratitude to Prof. Fernando Silva and Hugo Ribeiro, for allowing me to use the high-performance computing cluster of the Center for Research in Advanced Computing Systems (CRACS). I especially thank my Mom and Marta who have sacrificed for supporting me and provided unconditional love and encouragement. Finally, I would like to thank all my best friends for their friendship, loyalty and moments of personal grown. Apologies to anyone I forgot. Abstract The introduction of vehicle-to-vehicle and vehicle-to-infrastructure communications forming vehicular ad-hoc networks, enabled a new set of applications and services for Intelligent Transportation Systems (ITS). Due to the costs of setting up a real experiment, specially for large-scale scenarios, vehicular network simulators are cru- cial for the study and development of these technologies. There are a considerable number of possible solutions in the state-of-the-art, which differ essentially on the way the mobility and network simulation components are connected and on their level of interaction. However, the available solutions were not designed to fulfill the requirements of modern ITS applications, as well as to provide large-scale simulations. Although current network simulators are very powerful, being able to model wireless networks with a high level of detail, they have strong scalability limitations, being hard to simulate wireless networks with only a few thousand of nodes. The focus of this thesis is to solve these issues, developing solutions to enable efficient simulation of vehicular networks. We aim to provide researchers with new tools to study vehicular networks in large-scale scenarios, and to implement new applications that were very difficult to implement with the currently available tools. This work proposes a different approach to efficiently integrate traffic and network simulators, given the fact that not only the networking dynamics are greatly dependent on the mobility aspect, but also the network-enabled applications can influence the mobility patterns of ITS systems. Solutions for parallel microscopic traffic simulation, together with algorithms for fast neighbour finding and position updates during wireless simulations are also proposed, improving the efficiency of the presented simulation framework. Results show that the proposed solutions enable the simulation of large-scale vehicular networks, outper- forming the performance of other open-source simulators. During the course of this work, different ITS applications were also proposed and evaluated, such as a large-scale analysis of a self-organizing traffic control scheme, a dynamic taxi-sharing system and a taxi-stand recommendation system. The evaluation of an advanced driver assistance system for overtaking vision obstructing vehicles is also presented. 9 10 Resumo A introdu¸c~aode comunica¸c~oesve´ıculo-ve´ıculoe ve´ıculo-infraestrutura, formando redes veiculares ad-hoc, proporciona um conjunto de aplica¸c~oese servi¸cosaos Sistemas de Transporte Inteligente (ITS). Dado o elevado custo para elaborar uma experi^encia real, especialmente uma experi^enciaem grande escala, as ferramentas de simula¸c~ao s~aoessenciais para o estudo e desenvolvimento destas redes. Existe um n´umero consider´avel de solu¸c~oesno estado-da-arte que diferem, principalmente, no modo de liga¸c~aoe interac¸c~aoentre a simula¸c~aode mobilidade e a simula¸c~aode rede. Contudo, estas solu¸c~oesn~aoforam desenhadas para preencher os requisitos das aplica¸c~oesmais recentes. Embora sejam capazes de efectuar simula¸c~oescom um grande n´ıvel de detalhe, sofrem grandes limita¸c~oesem termos de escalabilidade, sendo dif´ıcilsimular redes sem-fios com pouco mais de mil n´os. Esta tese pretende resolver estes prob- lemas e desenvolver solu¸c~oesque permitam simular redes veiculares de grande-escala eficientemente ou desenvolver novas aplica¸c~oesque seriam dif´ıceisde desenvolver com as solu¸c~oesactualmente dispon´ıveis. Este trabalho prop~oeuma nova arquitectura para integra¸c~aode um simulador de mobilidade com simuladores de rede, dado que n~aos´o a din^amicadas comunica¸c~oesest´adependente da mobilidade, como as aplica¸c~oesde rede tamb´empodem influenciar os padr~oesde mobilidade. Neste trabalho tamb´em s~aopropostas solu¸c~oespara uma eficiente paraleliza¸c~aoda simula¸c~aode mobilidade, assim como algoritmos para procura eficiente de n´osvizinhos durante transmiss~oes sem-fios, aumentando a performance das simula¸c~oes.Os resultados obtidos mostram que as solu¸c~oesapresentadas possibilitam a simula¸c~aode redes veiculares de grande- escala de forma eficiente, superando a performance de outros simuladores. Durante a execu¸c~aodeste trabalho, s~aotamb´empropostas e avaliadas diferentes aplica¸c~oes, como um sistema auto-organizado de controlo de tr^ansitoe respectiva an´alise em grande-escala, um sistema din^amico para partilha de t´axise um sistema inteligente de recomenda¸c~aode pra¸casde t´axis. A avalia¸c~aode um sistema avan¸cadode auxilio `a ultrapassagem a ve´ıculosque obstruem a vis~aodo condutor ´etamb´emapresentada. 11 12 Contents Abstract 9 Resumo 11 List of Tables 18 List of Figures 21 1 Introduction 27 1.1 Contribution of this Thesis . 29 1.2 Thesis Structure . 31 2 Vehicular Networks 33 2.1 Architecture . 35 2.2 Wireless Access Technologies . 37 2.2.1 WLAN . 37 2.2.2 DSRC/WAVE . 38 2.2.3 WiMAX . 39 2.2.4 Cellular Networks . 39 2.3 Information Dissemination . 39 2.4 Summary . 41 13 3 Simulation Technology 43 3.1 Discrete-Time Simulation (DTS) . 45 3.2 Discrete-Event Simulation (DES) . 46 3.3 Network Simulation . 47 3.3.1 GloMoSim . 47 3.3.2 JiST/SWANS . 47 3.3.3 NS-2 . 48 3.3.4 NS-3 . 48 3.3.5 OMNET++ . 49 3.4 Mobility Simulation . 50 3.4.1 DIVERT . 52 3.4.2 SUMO . 53 3.5 VANET Simulators . 54 3.5.1 GrooveNet . 55 3.5.2 TraNS . 55 3.5.3 STRAW/SWANS . 56 3.5.4 NCTUns . 56 3.5.5 Veins . 57 3.5.6 iTETRIS . 58 3.6 Summary . 60 4 VNS: Vehicular Networks Simulator 61 4.1 Architecture . 64 4.2 Mobility Simulation . 69 4.2.1 Modelling Microscopic Simulation . 70 4.2.2 Vehicle Dynamics . 72 14 4.2.3 Lane Changing Models . 73 4.2.4 Intersection Control . 74 4.2.5 Human Response . 75 4.2.6 Traffic Generation . 75 4.3 Network Simulation Modules . 77 4.3.1 Simple Network Module . 77 4.3.2 NS-3 Network Module . 78 4.3.2.1 NS-3 simulation example . 79 4.3.2.2 NS-3 module implementation . 80 4.3.3 OMNET++ Network Module . 82 4.3.3.1 OMNeT++ simulation example . 83 4.3.3.2 OMNeT++ module implementation . 83 4.4 Integrating VNS with a Driving Simulator . 86 4.4.1 Integration Module . 87 4.4.2 Driving Simulator . 89 4.5 Visualization . 91 4.5.1 2D . 91 4.5.2 3D . 92 4.6 Analysis of a preliminary impact of VNS . 93 4.7 Conclusions . 95 5 Enabling Large Scale Simulations 97 5.1 Parallel Microscopic Traffic Simulation . 99 5.1.1 Related Work . 100 5.1.2 Parallel Microscopic Simulation . 101 5.1.2.1 Communication and Synchronization . 101 15 5.1.2.2 Dynamic Load Balancing . 102 5.1.2.3 Deterministic and Reproducible Simulations . 103 5.1.3 Evaluation . 104 5.1.3.1 San Francisco Bay Area Simulation . 104 5.1.3.2 Performance Comparison with other Simulators . 107 5.1.4 Conclusions . 108 5.2 Scalable VANET Simulations with NS-3 . 109 5.2.1 Problem Statement . 109 5.2.2 Improvements on the Network Simulator . 111 5.2.2.1 Updating the Tree . 112 5.2.2.2 Neighbor Finding . 113 5.2.3 Evaluation . 115 5.2.4 Related Work . 118 5.2.5 Conclusions . 119 6 Simulation of VANET Applications 121 6.1 Large Scale Beaconing Evaluation . 123 6.1.1 Validation of VNS simulations . 124 6.1.2 Beaconing evaluation in a Manhattan grid scenario . 127 6.1.3 Beaconing evaluation in the Porto scenario . 129 6.1.4 Performance comparison with Veins and iTETRIS . 130 6.2 Self-Organized Traffic Control . 134 6.2.1 Virtual Traffic Lights . 135 6.2.2 Simulation Evaluation .
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