VANET Simulation

Vehicular Ad-hoc Networks (VANET) are the subset of Wireless Ad-hoc networks specially introduced for the intelligent transportation system. It interconnects the massive range of vehicles in the distributed network. The main motive of Vanet Simulation is to increase vehicular interaction and driver safety in the case of undesired circumstances. Moreover, the VANET simulation comprises a mobility model and network simulator to analyze the simulated VANET model behaviour.

This page completely describes the VANET project simulation with supporting simulators!!!

Now, we can see the architecture of the VANET model. Generally, the VANET model encompasses five different layers such as physical, network, security, MAC, and application layers. These layers are differentiated based on their features and responsibilities to perform in vehicular communication. Below, we have given you some primary functions involved in each layer. 

Performance analysis of Vanet Simulation

VANET Architecture

  • Physical Layer
    • Modulation Type
    • Multiple Antenna
    • IEEE 802.11p Protocol
    • Spectrum Provisioning
  • Network Layer
    • Remodelling of geocast, multicast, broadcast, unicast
    • Routing on Multi-hop Communication
  • Security Layer
    • Data Privacy and Integrity
    • Authentication and Accessibility
    • Real-Time Limitations
    • Minimal Overhead
    • Anonymity Detection
  • Media Access Control (MAC) Layer
    • RR-ALOHA, IEEE 1609.4 and IEEE 802.11p Protocol
    • Prevention of Communication Collision
    • Consistent Medium Access
  • Application Layer
    • Web Connectivity
    • Vehicle-to-Vehicle Connectivity
    • Local Roadside Unit Connectivity

In addition, we have also given the notable characteristics of VANET Simulation and modelling. These characteristics play a key role in developing customized vehicular applications and services. Also, it directs the current VANET technologies towards future advancements. 

Specific Features for VANET Simulation

  • Enhancing the accuracy of vehicle position. For that, it utilizes several intelligent techniques of location reference to create local maps  
  • Enable to design and develop new protocols for V2V and V2I communications
  • Designing tools to find and analyze the technical problems related to the small and large-scale simulations
  • Able to develop intellectual model to control traffic control for quick identification of incidents / accidents for roadside / vehicle systems 
  • Empower to create different kinds of applications such as driver aids, mobility service, traffic and resource management, etc. 

What is VANET Simulation?

In general, the virtualization of the VANET environment incorporates 2 primary entities such as network simulator and a vehicular traffic simulator. Here, the network simulator is used to assess the network behaviour, and the traffic simulator is used to instigate the mobility models of deployed nodes. Next, we can see the reason behind the utilization of VANET simulation.

What are the needs of VANET Simulation?

  • VANET simulation tools allow you to check the performance of the VANET network at a minimum price without creating threats to the connected users
  • Enables to model and virtualize the emerging technologies as 5G, SDN, edge computing, etc. in the VANET framework to achieve maximum security
  • Helps to increase the VANET improvement in multiple aspects
  • Support you to develop any kind of complicated VANET scenarios
  • Furnished with macro and micro-mobility specifications
  • Allow creating VANET specific and open-source software and services
  • One developed mobility model can be simulated in various network configurations

We hope that you are clear about VANET architecture, features, vanet simulation, and their needs. Now, we can see the key points that are required to be noted while choosing the VANET simulator. Since the handpicked appropriate simulator provides accurate experimental results. 

How to select the VANET simulation tool?

  • For reducing the manual power and cost of real vehicular network investigation, everybody is moving on towards network simulation. 
  • For improving the network efficiency, the simulator helps to incorporate different channel models, mobility models, and driver behavior 
  • For achieving actual vehicular traffic with the expected outcome, it allows integrating the mobility models with network simulator
  • For checking the network behavior in different scenarios, simulators are used. Further, it is also capable to assess the complex infrastructure to yield accurate results than real testbeds.  

On the whole, VANET simulator selection needs more concern to accomplish real traffic flow with expected results. For your benefit, we have discussed more different VANET simulators in the upcoming sections. Certainly, it helps you to compare the tools with one another. Here, we have given you the things that are connected wholly to form the VANET simulation environment

VANET Simulation Environment

  • Communication Model
  • Signal Propagation Model
    • Stochastic and Deterministic Models
    • Mobile Obstructions Model (dynamic vehicles)
    • Fixed Obstructions Model (static vehicles, hills, building, etc.)
  • Node Mobility Model
    • Dedicated Traffic
      • Execution of Traffic flow (speed models, crossing control, etc.)
      • Varied Mobility Patterns (manhattan grid, road-restricted, random waypoint, etc.)
      • Vehicular Data Exchange (calamity simulation, lane shifting, etc.)
    • Trace-assisted Mobility
      • Artificial and Real-time Traces

Next, we can see the working procedure of the VANET model in simulation. From this, you can get an idea about how the VANET model is simulated in the VANET infrastructure. And, the procedure may vary based on the requirements of the project.

VANET Simulation Procedure
  • Set the VANET infrastructure by deploying N number of vehicles and Road Side Units (RSUs)
  • Start the simulation
  • Initiate the node mobility
  • Transmit the data packets from source node
  • Receive the data packets by destination node
  • End the Simulation

Our developers have more than enough practice in all possible precise results generating VANET simulation tools. So, we are adept to guide you in identifying the best-fitting tool for your handpicked VANET project. Below, we have listed the different varieties of VANET simulators for your awareness.

Types of VANET Simulators

  • Opnet Modeler
    • Support both trajectory and random mobility
    • For trajectory mobility model, each node encloses trajectory file
    • However it enables to handle and describe complicated node mobility, it is constrained with real-time mobility due to continuous nodes communications
  • TraNS (Traffic and Network Simulation Environment)
    • First tool to combine sumo assisted vehicular mobility with network simulator
    • In this, parse enable the connection between these tools through passing sumo output as input of NS-2.
    • Further, it also uses traceexporter tool from sumo to integrate with ns-2
  • SUMO
    • Integrate with VANET network for designing the road traffic
    • Further, include NetSim for designing IEEE WAVE / LTE
  • In Veins (Vehicles in Network Simulation)
    • Integrate sumo with omnet++ simulator for enabling bidirectional data exchange
    • Flexible to respond to actions of mobility modelling tool
  • TraNS + OPNET Modeler + VanetMobiSim:
    • TraNS used to simulate VANET environment
    • OPNET used to simulate and assess entire network
    • VanetMobiSim used to initiate the node mobility in the network
  • Swans++
    • VANET simulator tool with the prolonged features of straw and vehicular mobility
    • Here, the straw stands for Street Random Way point
    • Further, it utilizes realistic street map collected from street database
    • For instance: Topologically Integrated Geographic Encoding and Referencing (TIGER) database
  • GrooveNet
    • Extended tool of RoadNav simulator
    • Type of vehicular mobility simulator which is called as GrooveSim
    • Enable to design car-following model by incorporating realistic street map from tiger 

For illustration purposes, here we have selected the VANET MobiSim Tool as the sample one. In this, we have discussed the installation and architectural requirements. It makes you understand how the VANET MobiSim and network simulator are functioned together to meet their requirements, 

  • At first, install the VANET MobiSim in windows OS
  • Next, the mobility model generator make “.xml” file
  • Then, it produces the mobility model
  • After that, install the NS-2 in Linux OS
  • Next, produce the “.tcl” file for the purpose of simulation
  • Further, utilize cbrgen.tcl for primary “.tcl” file
  • Start the simulation of the VANET model
  • Then, produce the NS2 trace file and animate the model
  • At last, examine the trace file to assess the network performance

Simulation Architecture

  • In VANET MobiSim, the traffic generator produces the vehicular trace
  • Then, the produced trace file is transformed to the NS-2 network simulator
  • In Network Simulator, it creates the communication
  • In overall, traffic simulator and network simulator have two different functionalities. Here, vehicular mobility traces are produced by traffic simulator and data exchange infrastructure is designed by network simulator

Furthermore, our developers have highlighted few significant files that generate the traffic, analyze the network performance, trace the network simulation and animate the network communication. 

How does VANET MobiSim with NS2 simulation works?

  • VanetMobiSim-1.1 (Traffic Generator)
  • Vehicular Traffic Trace (.tr)
  • Network Traffic Trace (.tr) (Network Simulator)
    • Ns-2.35 TCL Script cbrgen.tcl
  • Simulation Trace (.tr)
  • Awk (Performance Fitor)
  • Simulation Results
  • Network Animator (.nam)

Other Tools for VANET Simulation

The first and foremost tool to appraise the network VANET performance is GrooveSim which is developed in C++. It is intended to design and predict the traffic flow in the network. Most importantly, it helps to examine the probability of real-world actions such as passing security messages. Additionally, the graphical interface of Matlab lets you get pictorial output as graphs.

Performance Analysis of VANET Simulation

In VANET, simulators are used to assess the efficiency of employed protocols and applications which yield huge data. Further, it also needs some special parameters for network evaluation. Through this, you can perform a comparative study of dissimilar environments. And, the parameters are:

  • Connection and Simulation Time 
  • No of Disconnection 
  • Throughput 
  • No of Tries / Packet 
Important Vanet Simulation Projects With Source Code

How to set the parameters for VANET Simulation?

Basically, every simulation tool of VANET is differing from each other because of its functionalities. Furthermore, it also supports various parameters to improve and assess network performance. Depends on the project needs, we need to choose the tool and its key parameters. Our developers are well-versed in identifying the appropriate tool.

OMNeT ++

  • Simulation Duration
  • Mobility Model
  • MAC layer
  • Number of nodes
  • Number of Iterations
  • Velocity (speed)
  • Propagation Model
  • Coverage Capacity

OMNET++ VEINS

  • Transmission Power
  • Control and Guard Subcarrier
  • Base Station and Vehicle Height
  • RSU and OBU height
  • Number of Vehicles and Subcarriers
  • UE and ENodeB Transmission
  • Simulation Duration and Area
  • Pedestrian Walking and Vehicle Urban Speed
  • Resource Block
  • IEEE 802.11p (BW/frequency)
  • LTE vehicles and BS antenna type
  • Beacon Interval
  • Propagation Analogue Model
  • Header Packet Size
  • maxOffset
  • Data Transfer Rate

NS2 with SUMO

  • Transport Protocol (TCP, UDP)
  • Map Model (OSM)
  • Routing Protocol (DSR, AODV, DSDV)
  • Data Transfer Rates
  • Minimum and Maximum Speed
  • Application Type
  • Propagation Model
  • Code Rate
  • Number of Vehicles
  • Simulation Duration
  • Modulation
  • Packet Size

NS2

  • Data Transmit Range
  • MAC Protocol
  • Count of Vehicles
  • Channel bandwidth (capacity)
  • Vehicle Velocity
  • Simulation Coverage and Duration
  • Radio Frequency (RF)
  • CBR Flow of Data
  • Propagation Model

Moreover, here our research team has given the emerging technologies that are growing fast in integrating with the VANET network. These areas have attained special places in VANET Simulation research. Our experts have more unique research ideas in the following areas to create futuristic VANET development

What are the integrated technologies supporting VANET?

  • 5G Network
  • Autonomous Vehicles
  • Fog-Edge Computing
  • Software Defined Network (SDN)
  • Unmanned Aerial Vehicles (UAV)

Due to the VANET unique capabilities, it rapidly gains the attentions of scholars who are interested to do something new in the field of VANET. Also, this field motivates the scholars to develop real-time vehicular simulation through evolving security technologies and tools. In truth, our resource team has updated their knowledge on all these technological developments to support you in all respects of VANET. So, make use of this chance to get the masterwork in your research by contacting us.

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Research Topics Project Paper Thesis
3D Underwater WSN 150 499 541
Hybrid Beamforming 110 398 432
Intelligent Agent WSN 135 412 510
Blockchain technology 121 467 496
Optical Networks 149 398 465
Vehicular sensor Network 250 491 534
Industrial IoT 114 378 431
Service Discovery 170 419 489
Named Data Networking 121 386 423
SDN-NDN 110 427 498
D2D Communication 131 389 425
M2M Communication 108 389 411
UWB communication 124 495 510
5G Network Slicing 137 437 492
Delay Tolerant Network 105 469 533
Multi-Microgrid 111 326 379
Content-centric network 100 296 304
5G Beyond networks 131 379 409
Cloud-RAN 127 352 389
Fog-RAN 145 310 378
FANET 178 395 400
Cognitive adhoc network 153 325 363
Vehicular NDN 175 310 425
Multimedia sensor network205 275 315
V2X communication 151 200 308
Software-defined WSN 176 248 358
5G 201 289 365
Fibre Channel / Cellular / 5G topics
Cellular Networks 185 235 397
CRN 204 268 348
IoT 163 287 395
Intrusion Detection system110 257 348
LiFi 101 279 386
LTE 159 208 345
MANET 175 247 395
MIMO 142 298 354
Mobile Computing 114 254 308
RPL 189 275 357
SDN 109 258 346
VANET 152 278 359
Vertical Handover 108 241 367
Wireless Body Area Network121 198 348
Wireless Communication 178 248 371
Wireless Sensor Networks106 213 369
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Computer Networking Domains

  • Wireless Sensor Networks (WSN)
  • Mobile Ad-hoc Networks (MANET)
  • Vehicular Ad-hoc Networks (VANET)
  • Internet of Things (IoT)
  • 5G Networks
  • 6G Wireless Communication
  • Software Defined Networking (SDN)
  • Network Function Virtualization (NFV)
  • Cognitive Radio Networks
  • Wireless Mesh Networks
  • Delay Tolerant Networks (DTN)
  • Underwater Sensor Networks (UWSN)
  • Body Area Networks (BAN)
  • Smart Grid Communication
  • Satellite Communication Networks
  • LTE/4G Networks
  • Mobile Communication Systems
  • Edge Computing in Networking
  • Fog Networking
  • Cloud-based Network Architecture
  • Green Networking
  • Opportunistic Networks
  • Multicast and Broadcast Routing
  • Network Topology Design
  • Network Performance Analysis
  • Network Simulation and Modeling
  • Network Protocol Design
  • Wireless Multimedia Sensor Networks
  • Routing Protocols (AODV, DSR, OLSR, etc.)
  • QoS in Wireless Networks
  • Mobility Models in Networks
  • Cross-layer Optimization
  • Antenna Design & Beamforming
  • IoT-enabled Healthcare Networks
  • LPWAN (LoRa, Sigfox, NB-IoT)
  • Millimeter-Wave Communication
  • MIMO Systems
  • VANET Security
  • Network Traffic Management
  • Congestion Control Mechanisms
  • Spectrum Allocation & Management
  • Smart City Communication
  • Multi-hop Networks
  • IoT Device Communication
  • Wireless Interference Management
  • Satellite-IoT Integration
  • Multi-RAT (Radio Access Technology) Networks
  • Hybrid Networks
  • Dynamic Spectrum Access
  • Intermittently Connected Networks

Cybersecurity Domains

  • Network Security
  • Cyberattack Detection
  • Intrusion Detection Systems (IDS)
  • Intrusion Prevention Systems (IPS)
  • Distributed Denial-of-Service (DDoS) Mitigation
  • Firewall Architecture and Design
  • Security in IoT Networks
  • Authentication and Access Control
  • Blockchain for Network Security
  • Data Encryption Techniques
  • Wireless Security Protocols
  • Secure Routing in Ad-hoc Networks
  • Trust Management in Networks
  • Cyber Threat Intelligence
  • Honeypots and Honeynets
  • AI-Based Threat Detection
  • Zero Trust Security Architecture
  • Malware Detection and Analysis
  • Cloud Security
  • Fog and Edge Security
  • Deep Packet Inspection
  • Privacy Preservation in Networking
  • Steganography in Network Communication
  • Cyber Forensics
  • Risk Assessment and Vulnerability Analysis
  • Secure IoT Communication
  • Botnet Detection in Networks
  • Phishing Attack Prevention
  • Insider Threat Detection
  • Identity Management Systems
  • Cryptographic Protocols
  • Public Key Infrastructure (PKI)
  • Secure Network Virtualization
  • Web Application Security
  • Wireless Intrusion Detection
  • Adaptive Security Mechanisms
  • SDN-Based Network Security
  • Anomaly-Based Detection Systems
  • Secure Group Communication
  • Ransomware Protection
  • DNS Spoofing and Protection
  • Man-in-the-Middle (MITM) Attack Defense
  • Security in SCADA Networks
  • IoT Botnets and Countermeasures
  • Threat Modeling and Simulation
  • Biometric Authentication in Networks
  • Secure Firmware Updates in IoT
  • Endpoint Detection and Response (EDR)
  • Data Loss Prevention (DLP) in Networks
  • Secure Wireless Mesh Networks

Network Communication Domains

  • Channel Allocation Strategies
  • MAC Layer Protocols
  • Medium Access Control in WSN
  • TDMA, FDMA, CDMA-Based Communication
  • Wireless Interference Modeling
  • Traffic Engineering in Networks
  • Cross-Layer Communication Design
  • Signal Propagation Models
  • Network Coding Techniques
  • Multicast Communication
  • Multi-Channel Communication
  • Hybrid Communication Models
  • TCP/IP Performance Tuning
  • Adaptive Data Transmission
  • Smart Antenna Communication
  • Cooperative Communication
  • Delay-Tolerant Communication
  • Real-Time Data Transmission
  • Context-Aware Communication
  • Ultra-Reliable Low Latency Communication (URLLC)
  • Energy-Aware Communication Protocols
  • Congestion-Aware Routing
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  • Cluster-Based Communication
  • Latency Optimization in Networks
  • Bandwidth Management Techniques
  • Fault-Tolerant Communication Systems
  • Communication in Smart Homes
  • Mobile-to-Mobile Communication
  • Wi-Fi Offloading Techniques
  • Dynamic Topology Control
  • Sensor-to-Base Station Communication
  • Communication in Swarm Robotics
  • Time Synchronization in Wireless Networks
  • Mobility-Driven Communication
  • Real-Time Streaming over Networks
  • Network Communication in Drones (UAVs)
  • Multi-Hop Relay Communication
  • Heterogeneous Network Communication
  • Device-to-Device (D2D) Communication
  • Application Layer Protocols
  • Cognitive Communication Systems
  • Energy Harvesting Communication
  • Full Duplex Communication
  • Multimodal Network Communication
  • Autonomous Vehicle Communication
  • Communication in Disaster Recovery Networks
  • Reliable Data Broadcasting in Wireless Networks

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  • Physical Layer
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  • Traffic Analysis Attack
  • Sniffer Attack
  • SS7 Attack
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  • Small Cell Nets
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  • Nearest Antenna Selection
  • Spatial Modulation
  • PAPR Mitigation
  • Multiple Access
  • Filtered OFDM
  • MAC Frame Design
  • In-body, On-body & Off-body
  • Emergency Data Prediction
  • Remote Patient Monitoring
  • Energy Aware Resource Allocation
  • Power Optimized Data Transmission
  • Flow Rule Placement
  • Multimedia Flows Routing
  • Buffer Management
  • Network Traffic Analysis
  • Dynamic Offloading
  • Controller Placement
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  • Vehicle Traffic Analysis
  • Network Penetration Testing
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  • Task Offloading Decision
  • Traffic aware Routing
  • Network Privacy
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  • Network Traffic Balancing
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  • Types of Forensics
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