How to Simulate Hierarchical Star Topology Using MATLAB

To simulate a Hierarchical Star Topology in MATLAB has includes to generate a network in which the star topologies are arranged in multiple layers. In a hierarchical star topology, each and every cluster has a central hub, and these hubs are associated to a higher-level hub, that creates a hierarchy. This kind of topology is usual in large networks in which each cluster performs by way of a local network associated to a central core network.

Here is a brief approach to simulate this process:

Steps to Simulate a Hierarchical Star Topology

1. Define the Multi-Layer Star Structure:
   • Generate multiple clusters; everyone is organized in a star topology with a central hub.
   • Associate the hubs of every cluster to a main hub that creates a higher-level star topology.
2. Simulate Data Transmission:
   • Enable nodes within a cluster to interact via their local hub.
   • Execute routing via the main hub if interaction is essential among different clusters.
3. Implement Transmission Delays and Routing:
   • Estimate transmission latency within clusters and among clusters according to distance.
   • Measure the routing path by way of data flows from an origin node to a destination node, travels via hubs as essential.
4. Visualize Network Layout and Transmission Activity:
   • Measure the parameters like successful transmissions, delays, and routing paths.
   • Utilize MATLAB plots to envision the ordered star layout and data flow.

Example Code for Simulating a Hierarchical Star Topology

In this sample, we utilize three star clusters associated to a central hub.

% Parameters for Hierarchical Star Topology Simulation

numClusters = 3;               % Number of star clusters

nodesPerCluster = 4;           % Number of nodes per star cluster (including the local hub)

totalNodes = numClusters * (nodesPerCluster – 1) + 1; % Total nodes including main hub and local hubs

distanceWithinCluster = 50;    % Distance from nodes to local hub

distanceBetweenClusters = 150; % Distance from local hubs to main hub

propagationSpeed = 2e8;        % Propagation speed in meters per second

transmissionProbability = 0.3; % Probability of initiating a transmission at each node per time step

simulationTime = 20;           % Duration of the simulation in seconds

% Initialize Node Positions

mainHubPosition = [0, 0]; % Main hub at the center

nodePositions = mainHubPosition;

clusterHubs = [];

% Set up positions for clusters and nodes within clusters

for i = 1:numClusters

angle = (i – 1) * (2 * pi / numClusters);

clusterHubPosition = mainHubPosition + [cos(angle), sin(angle)] * distanceBetweenClusters;

clusterHubs = [clusterHubs; clusterHubPosition];

nodePositions = [nodePositions; clusterHubPosition]; % Add cluster hub position

for j = 2:nodesPerCluster

nodeAngle = 2 * pi * (j – 2) / (nodesPerCluster – 1);

nodePosition = clusterHubPosition + distanceWithinCluster * [cos(nodeAngle), sin(nodeAngle)];

nodePositions = [nodePositions; nodePosition];

end

end

% Define Connection Matrix

connectionMatrix = zeros(totalNodes);

mainHub = 1;

% Connect main hub to each cluster hub

for i = 1:numClusters

clusterHub = i * (nodesPerCluster – 1) + 1;

connectionMatrix(mainHub, clusterHub) = 1;

connectionMatrix(clusterHub, mainHub) = 1;

end

% Connect nodes within each cluster in a star pattern

for i = 1:numClusters

clusterHub = i * (nodesPerCluster – 1) + 1;

for j = 1:(nodesPerCluster – 1)

node = clusterHub + j;

connectionMatrix(clusterHub, node) = 1;

connectionMatrix(node, clusterHub) = 1;

end

end

% Calculate Transmission Delay for each Connection

delayMatrix = (connectionMatrix * distanceWithinCluster) / propagationSpeed;

% Initialize Transmission Log

transmissions = zeros(totalNodes, simulationTime);

% Routing Helper Function

function path = hierarchicalRouting(src, dst, connectionMatrix, mainHub)

% Check if source and destination are in the same cluster

if connectionMatrix(src, dst) == 1

path = [src, dst];

elseif connectionMatrix(src, mainHub) == 1 && connectionMatrix(dst, mainHub) == 1

% Route through main hub if they are in different clusters

path = [src, mainHub, dst];

else

path = [];

end

end

% Simulate Data Transmission in Hierarchical Star Topology

for t = 1:simulationTime

for node = 2:totalNodes

if rand() < transmissionProbability

% Randomly select a destination node

destNode = randi([2, totalNodes]);

if destNode ~= node

% Get the routing path using hierarchical routing

path = hierarchicalRouting(node, destNode, connectionMatrix, mainHub);

delay = (length(path) – 1) * distanceWithinCluster / 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 Hierarchical Star Topology Layout

figure;

gplot(connectionMatrix, nodePositions, ‘-o’);

hold on;

text(nodePositions(:, 1), nodePositions(:, 2), arrayfun(@num2str, 1:totalNodes, ‘UniformOutput’, false));

title(‘Hierarchical Star Topology Layout’);

xlabel(‘X Position’);

ylabel(‘Y Position’);

hold off;

% Visualize Transmission Activity Over Time

time = 1:simulationTime;

figure;

imagesc(transmissions);

colorbar;

title(‘Transmission Activity Over Time in Hierarchical Star Topology’);

xlabel(‘Time (s)’);

ylabel(‘Node ID’);

Explanation of the Code

• Parameters:
  • numClusters and nodesPerCluster describe the amount of clusters and nodes per cluster that contain a local hub in each cluster.
  • distanceWithinCluster and distanceBetweenClusters set the distances among  nodes inside a cluster and among cluster hubs and the main hub.
• Connection Matrix:
  • connectionMatrix is builds to denotes the hierarchical star topology, that includes:
    • Every cluster hub is associated to the main hub.
    • Nodes inside each cluster are associated to their particular cluster hubs in a star layout.
• Data Transmission Simulation:
  • At every time step, all nodes have a gamble to begins a data transmission to a arbitrarily chosen destination node.
  • The hierarchicalRouting function validates if the origin and destination nodes are in the similar cluster. If they are not, documents are transmitted via the main hub.
• Propagation Delay Calculation:
  • delayMatrix keeps the propagation latency for each link according to the distance among nodes and the transmission speed.
• Visualization:
  • The initial plot illustrates the layout of the ordered star topology, with nodes, cluster hubs, and the main hub.
  • The second plot demonstrates routing activity over time, with every row illustrating a node and each column denotes a time step.

Analysis and Extension Ideas

• Multi-Level Hierarchy: Expand the hierarchy by incorporating another layer of hubs that generates a three-tier network.
• Variable Node Density: Enable every cluster to have a diverse amount of nodes, replicates uneven network clusters.
• Congestion Analysis: Measure traffic at the main hub to evaluate the congestion and bottleneck concerns.
• Fault Tolerance: Replicate node or link failures and learn the effects on transmission and data flow.
• Traffic Prioritization: Execute traffic selection at the main hub to offer preference to particular kinds of data or nodes.

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