How to Start FANET Projects Using NS3

To start the Flying Ad-hoc Networks (FANETs) that include a UAVs (Unmanned Aerial Vehicles) or drones network, which interact with each other and potentially along with a ground control station. FANETs are utilized within diverse applications such as surveillance, disaster management, and environmental monitoring. To setting up a FANET project in NS3, follow these steps.

Steps to Start FANET Projects in NS3

Step 1: Set Up NS3 and Required Modules

  1. Download and Install NS3:
    • Form the NS3 official page, we can download the new version of NS3 and then make sure that it is configured properly including all dependencies.
  2. Install Mobility Models:
    • NS3 contains built-in mobility models, which are significant for replicating the dynamic nature of FANETs. UAVs have high mobility, thus we utilize the models like RandomWaypointMobilityModel or GaussMarkovMobilityModel that are available within NS3.
  3. Consider Open-Source FANET Extensions (Optional):
    • For FANETs, certain research groups contain enhanced extensions, which probably compatible with NS3. Confirm for any available FANET modules or online scripts that should offer certain functionalities such as 3D mobility models or UAV-specific interaction protocols.

Step 2: Define FANET Project Objectives

  1. Identify Your Project Goals:
    • In FANET projects, general objectives contain:
      • Routing Efficiency: Measure the diverse ad hoc routing protocol’s performance within a highly dynamic UAV environment.
      • Latency and Reliability: Experiment interaction delays and packet loss within drone-to-drone and drone-to-ground communication.
      • Network Scalability: We estimate the network performance like the amount of UAVs maximizes.
      • Mobility and Coverage: Measure how mobility impacts the connectivity and coverage area.
  2. Select FANET-Specific Metrics:
    • For FANET assessment, describe parameters such as packet delivery ratio, latency, throughput, network partitioning frequency, and path stability.

Step 3: Set Up Network Topology

  1. Define UAV Nodes:
    • In the FANET, denote UAVs utilising NS3 nodes.
    • Set up nodes including Wi-Fi or LTE modules to allow interaction. For ad hoc networks, Wi-Fi module is generally utilized, however if we need to test with cellular connectivity, LTE is also a choice.
  2. Configure UAV Mobility Models:
    • Select suitable mobility models replicating the UAV movement patterns:
      • RandomWaypointMobilityModel: For random and free-movement situations, we can use this model.
      • GaussMarkovMobilityModel: For realistic, smooth movement including variable speed and direction.
      • 3D Mobility: If we want more realistic UAV flight paths such as by using a custom script then modify a 3D mobility model.
  3. Set Up Communication Links:
    • Set up communication ranges and link parameters deliberating normal drone-to-drone interaction limitations.
    • Replicate real-world FANET characteristics to modify the transmission power and signal range.

Step 4: Implement FANET Protocols

  1. Routing Protocols:
    • Introduce connectivity among UAVs to utilize ad hoc routing protocols such as OLSR (Optimized Link State Routing) or AODV (Ad hoc On-Demand Distance Vector).
    • Test with diverse routing protocols to observe which does best within a FANET environment since high mobility frequently directs to the common route changes.
  2. Layer Configuration:
    • For FANET communication, we can utilize the UDP protocol as it is frequently used in low-latency applications, while TCP can also be utilized if reliability is crucial more than speed.
    • In the Wi-Fi or LTE module, set up MAC and PHY layer metrics to modify the transmission range, frequency, and data rates.

Step 5: Set Up UAV Payload and Ground Control Station (Optional)

  1. Simulate UAV Payload Applications:
    • Make applications on UAV nodes signifying the data collection or to observe tasks like periodic data transfer or streaming.
    • Set up traffic patterns according to the application scenario, which replicate the real-time or periodic data transfer.
  2. Implement a Ground Control Station (GCS):
    • If the scenario needs a GCS then configure it like a separate NS3 node and also set it up interacting with the UAVs. For data collection or command/control communication, GCS can function as a central hub.

Step 6: Run Simulation Scenarios

  1. Define Test Scenarios:
    • Make diverse situations to experiment different FANET features, like:
      • High Mobility: Replicate the high-speed UAV movement measuring routing protocol performance.
      • Network Density Variations: Experiment the impact of maximizing or minimizing the volume of UAVs on network connectivity.
      • Obstacle Interference: Launch obstacles or restricted connectivity areas to monitor the adaptability of network.
  2. Configure Traffic and QoS:
    • Execute diverse kinds of traffic at UAV nodes like streaming (for surveillance) or periodic updates (for environmental monitoring).
    • Configure QoS parameters if required, based on the criticality of the data to be sent.

Step 7: Collect and Analyze Performance Metrics

  1. Gather Simulation Data:
    • Collect data on performance parameters such as latency, packet delivery ratio, throughput, and route changes to utilize NS3’s tracing and logging tools.
    • When UAVs lose connectivity, examine network partitioning frequency and we assess path stability for each routing protocol.
  2. Evaluate Performance:
    • Equate the routing protocol’s performance according to the select parameters. For example, AODV may offer lower latency however higher packet loss in high mobility conditions whereas OLSR should provide additional stable routes yet with a trade-off in latency.

Step 8: Optimize and Experiment Further

  1. Adjust Protocol Parameters:
    • Modify routing parameters, transmission power, and mobility parameters, according to the outcomes enhancing the network performance.
  2. Experiment with Advanced FANET Concepts:
    • Test with advanced aspects like multi-UAV cooperation, hierarchical routing, or edge computing on UAVs if applicable.
    • We replicate the failover mechanisms to experiment how the network replies to the node failures.
  3. Introduce Machine Learning (Optional):
    • If project includes the AI-based adaptive networking within FANETs then incorporate simple machine learning algorithms such as for predictive routing or adaptive mobility models.

In this manual, we successfully delivered the procedures to execute and examine the FANET Projects using NS3 tool that UAVs (Unmanned Aerial Vehicles) or drones network. If you did like to know more details regarding this process we will provide it.

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