To Simulate the Irregular topology in MATLAB has need to includes to generate the networks in which nodes and their associations to designed the plan is not to track the structed outline such as grid or ring. Irregular topologies are generally utilizing the real-world networks in which extra terms of the nodes to certain necessities instead of the predefined pattern for example ad hoc networks, sensor networks or randomly deployed IoT networks.
The give below following how to replicate the essential Irregular topology in MATLAB.
Steps to Simulate an Irregular Topology
- Define Node Placement and Connections:
- The nodes position arbitrarily situated in a 2D space.
- State the association among nodes according to the conditions such as distance thresholds or random probability.
- Simulate Data Transmission:
- The nodes permit to arbitrarily begins to transmit the information to additional nodes.
- If direct associations are not possible offered to execute the routing among nodes.
- Implement Transmission Delays:
- To evaluate the communication latency, create on the distance among nodes and propagation speed.
- To monitor the data paths and latency particularly routing is required for the multi-hop.
- Visualize Network Layout and Transmission Activity:
- Follow the metrices such as successful transmissions, delays, routing paths, and traffic patterns.
- Utilizing the MATLAB tool to plot the envision the irregular layout, connection patterns, and data flow.
Example Code for Simulating an Irregular Topology
In this sample we placed the nodes arbitrarily in the interior of particular area to create the connections according to the distance threshold. The nodes are interact with each other across exact links if they are need to the threshold and then routes by additional nodes.
% Parameters for Irregular Topology Simulation
numNodes = 15; % Number of nodes in the network
areaSize = 100; % Size of the square area for node placement
distanceThreshold = 30; % Maximum distance for direct connection between nodes
propagationSpeed = 2e8; % Propagation speed in meters per second
transmissionProbability = 0.3; % Probability of initiating a transmission per time step
simulationTime = 20; % Duration of the simulation in seconds
% Randomly Position Nodes within the Area
nodePositions = areaSize * rand(numNodes, 2);
% Define Connection Matrix Based on Distance Threshold
connectionMatrix = zeros(numNodes);
for i = 1:numNodes
for j = i+1:numNodes
distance = norm(nodePositions(i, 🙂 – nodePositions(j, :));
if distance <= distanceThreshold
connectionMatrix(i, j) = 1;
connectionMatrix(j, i) = 1; % Symmetric connection
end
end
end
% Calculate Propagation Delays for Each Link
delayMatrix = (connectionMatrix * distanceThreshold) / propagationSpeed;
% Initialize Transmission Log
transmissions = zeros(numNodes, simulationTime);
% Routing Helper Function Using Breadth-First Search (BFS)
bfsRoute = @(src, dst) bfsRoutingPath(src, dst, connectionMatrix);
% Simulate Data Transmission in Irregular Topology
for t = 1:simulationTime
for node = 1:numNodes
if rand() < transmissionProbability
% Randomly select a destination node
destNode = randi(numNodes);
if destNode ~= node
% Get the routing path using BFS if not directly connected
path = bfsRoute(node, destNode);
delay = (length(path) – 1) * distanceThreshold / propagationSpeed;
% Log transmissions along the path
for p = 1:length(path) – 1
transmissions(path(p), t + p – 1) = 1; % Transmission at each hop
end
disp([‘Time ‘ num2str(t) ‘s: Node ‘ num2str(node) ‘ sent data to Node ‘ num2str(destNode) …
‘ via path [‘ num2str(path) ‘] with delay ‘ num2str(delay) ‘ seconds’]);
end
end
end
end
% Visualize Irregular Topology Layout
figure;
gplot(connectionMatrix, nodePositions, ‘-o’);
title(‘Irregular Topology Network Layout’);
xlabel(‘X Position’);
ylabel(‘Y Position’);
hold on;
text(nodePositions(:, 1), nodePositions(:, 2), arrayfun(@num2str, 1:numNodes, ‘UniformOutput’, false));
hold off;
% Visualize Transmission Activity Over Time
time = 1:simulationTime;
figure;
imagesc(transmissions);
colorbar;
title(‘Transmission Activity Over Time in Irregular Topology’);
xlabel(‘Time (s)’);
ylabel(‘Node ID’);
% Breadth-First Search (BFS) Routing Helper Function
function path = bfsRoutingPath(src, dst, connectionMatrix)
% Initialize BFS structures
numNodes = size(connectionMatrix, 1);
visited = false(1, numNodes);
parent = zeros(1, numNodes);
queue = src;
visited(src) = true;
% BFS to find the shortest path
while ~isempty(queue)
currentNode = queue(1);
queue(1) = []; % Dequeue
% Check if destination is reached
if currentNode == dst
break;
end
% Explore neighbors
neighbors = find(connectionMatrix(currentNode, 🙂 == 1);
for neighbor = neighbors
if ~visited(neighbor)
visited(neighbor) = true;
parent(neighbor) = currentNode;
queue(end+1) = neighbor; % Enqueue
end
end
end
% Construct path from src to dst using parent pointers
path = dst;
while path(1) ~= src
path = [parent(path(1)), path];
end
end
Explanation of the Code
- Parameters:
- numNodes requires the total of nodes in the network, and distanceThreshold expresses the determined distance for direct links.
- Node Placement:
- Nodes are arbitrarily located inside a four-sided range described by areaSize.
- Connection Matrix:
- connectionMatrix states clear-cut networks among nodes constructed on the distanceThreshold. The two nodes are distance among less than or equal to the threshold then they are associated.
- Data Transmission Simulation:
- A stage of each period has possibility for each node to begins the information transmit to choose the destination node randomly.
- The exact relations are not accessible else Breadth-First Search (BFS) routing method is employed to discovery a multi-hop path.
- Propagation Delay Calculation:
- delayMatrix computes the latency for individually connection according to the supreme distance and the propagation speed
- Visualization:
- Each node demonstrating the relations to initially plot to displays the irregular topology layout.
- The second plot displays the communication action through time in which each row and column signifies a node and the time step.
Analysis and Extension Ideas
- Variable Link Quality: Each connection to allocate the random propagation latency to replicate the unpredictability of connection quality.
- Dynamic Network: The simulation model to further active and moving the network during the nodes are enhance or eliminate.
- Congestion and Load Analysis: The number of communications to follow the per node to classify the network traffic and evaluate the load distribution.
- Advanced Routing Algorithms: Apply more sophisticated routing technique, like as A* or Dijkstra’s method, for the finding the best path.
- Failure Simulation: To replicate node or connections loss to examine the impacts on routing their network dependability.
In this guide we demonstrated the procedures to simulate and implements the Irregular Topology Projects that are utilized in MATLAB tool and also, we provide the sample codes, extension tools and ideas of this project and we offer the tools to execute the simulations.
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