Steps to Implement Cognitive Ad Hoc Network in OMNeT++

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How to Implement Cognitive adhoc network in OMNeT++

To implement the Cognitive Ad-Hoc Network (COGNET) in OMNeT++ requires multiple key steps. Here, we offer the step-by-step implementation in the following below:

Step-by-Step Implementation:

  1. Set Up OMNeT++
  1. Install OMNeT++:
    • Make sure to install the install OMNeT++.
    • Follow the installation instructions provided for the system.
  2. Install INET Framework:
    • Install INET framework that offers models for network protocols and devices.
    • Unzip the INET framework inside the OMNeT++ workspace.
    • Open OMNeT++ IDE, import the INET project, and build it.
  1. Design the Cognitive Ad-Hoc Network Architecture
  1. Define the Network Structure:
    • Identify the components of COGNET like cognitive nodes and possibly primary users.
    • Define the communication protocols and data flow amongst the components.
  2. Create the Network Nodes:
    • Expand existing INET nodes or create new ones for specific components (like Cognitive Nodes).
    • Define the parameters and properties of these nodes (for instance: spectrum sensing, decision-making).
  1. Develop the Simulation Modules
  1. Cognitive Node Module:
    • Cognitive nodes needs a new module or extend an existing one for cognitive nodes.
    • Implement cognitive functionalities like spectrum sensing, dynamic spectrum access, and decision-making algorithms.
  2. Primary User Module:
    • Define a module to signifies the primary users (if applicable).
    • Make sure that this module can interact and coexist with cognitive nodes.
  1. Implement Communication Protocols
  1. Define Communication Interfaces:
    • Define the interfaces for communication amongst cognitive nodes and between cognitive nodes and primary users.
    • Use INET’s message-passing system to execute data exchange mechanisms.
  2. Simulate Network Traffic:
    • Simulate the data and control messages among the cognitive nodes and primary users by building traffic generators.
    • Execute algorithms for spectrum management and communication in the COGNET.
  1. Implement Cognitive Functions
  1. Spectrum Sensing:
    • Detect the presence of primary users by generating algorithms for spectrum sensing.
    • Implement these algorithms in the cognitive nodes.
  2. Spectrum Decision:
    • Select the best available spectrum by generating decision-making algorithms.
    • Implement these algorithms in the cognitive nodes.
  3. Spectrum Mobility:
    • Implement mechanisms for cognitive nodes to switch frequencies when a primary user is detected.
    • In the course of spectrum mobility, make sure that the communication is seamless.
  1. Configure the Simulation
  1. Network Configuration File (NED):
    • Write NED files to define the network topology and configuration.
    • Identify the types and connections of nodes in the network.
  2. Simulation Configuration File (INI):
    • Create INI files to identify simulation parameters like simulation time, node properties, spectrum sensing parameters, and logging options.
    • Configure various situations to examine the performance of your COGNET implementation.
  1. Run and Analyze the Simulation
  1. Run the Simulation:
    • Compile and run the simulation using OMNeT++ IDE.
    • Monitor the simulation for any errors or unexpected behavior.
  2. Collect and Analyze Results:
    • Use OMNeT++’s built-in analysis tools to collect simulation data.
    • Analyze metrics includes latency, throughput, spectrum utilization, and interference to evaluate the performance of your COGNET implementation.

Example Code Snippets

Here are some example snippets to give you an idea of what the configuration files might look like:

NED File (COGNET.ned)

package cognet;

import inet.node.adhoc.AdhocHost;

import inet.mobility.single.RandomWaypointMobility;

import inet.node.inet.Router;

network COGNET {

submodules:

cognitiveNode[10]: AdhocHost {

@display(“p=100,100;i=block/circle”);

mobility.typename = “RandomWaypointMobility”;

mobility.initialX = uniform(0, 1000);

mobility.initialY = uniform(0, 1000);

}

primaryUser: Router {

@display(“p=500,500;i=block/router”);

}

connections:

for i=0..9 {

cognitiveNode[i].pppg++ <–> primaryUser.pppg++;

}

}

INI File (omnetpp.ini)

[General]

network = cognet.COGNET

sim-time-limit = 1000s

*.cognitiveNode*.mobility.speed = uniform(5, 10)mps

*.cognitiveNode*.mobility.updateInterval = 0.1s

*.cognitiveNode*.mobility.constraintAreaMinX = 0m

*.cognitiveNode*.mobility.constraintAreaMaxX = 1000m

*.cognitiveNode*.mobility.constraintAreaMinY = 0m

*.cognitiveNode*.mobility.constraintAreaMaxY = 1000m

*.primaryUser.numCognitiveNodes = 10

# Additional parameters for traffic generation, spectrum sensing, and node properties

In this script, we provided the essential information on how to set up and implement the cognitive adhoc network using OMNeT++. If you need any added details of cognitive adhoc network, we will provide you.

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