How to Simulate Hierarchical Topology Projects Using MATLAB

To simulate a hierarchical topology using MATLAB that encompasses to make a network with many layers in which each layer contains diverse kinds of nodes that are associated within a hierarchical manner. Hierarchical topologies are generally utilized in networks, which need structured data flow and centralized control, like campus networks or enterprise environments.

In a hierarchical topology, nodes are arranged in levels, like core, distribution, and access layers:

  • Core layer: Handles high-speed traffic and interconnects distribution layers.
  • Distribution layer: Combines information from access nodes and it offers routing among access nodes.
  • Access layer: Associates end devices and furnishes access to the network.

We follow the given instruction that helps how to simulate a simple hierarchical topology with MATLAB.

Steps to Simulate a Hierarchical Topology

  1. Define the Hierarchical Structure:
    • Make nodes and organize them into diverse layers that are core, distribution, and access.
    • Describe the connections among nodes in each layer and between layers.
  2. Simulate Data Transmission:
    • Select nodes within the access layer to launch data transmission to nodes in other layers.
    • Execute a routing mechanism to enable the information to flow via distribution and core layers.
  3. Implement Transmission Delay and Routing Paths:
    • Compute transmission delays according to the layer hierarchy and distances.
    • From the access layer via the distribution layer to the core layer, we monitor the data path.
  4. Visualize Network Traffic and Performance:
    • Monitor network parameters like transmission success, delay, and routing path.
    • Envision the transmission paths and network load using MATLAB plots.

Example Code for Simulating a Hierarchical Topology

Following instance illustrates a basic 3-layer hierarchical topology with core, distribution, and access nodes.

% Parameters for Hierarchical Topology Simulation

numCoreNodes = 2;                  % Number of nodes in the core layer

numDistributionNodes = 4;           % Number of nodes in the distribution layer

numAccessNodes = 8;                 % Number of nodes in the access layer

simulationTime = 30;                % Duration of the simulation in seconds

dataRate = 1000;                    % Data rate in bits per second

packetSize = 100;                   % Packet size in bits

distanceBetweenLayers = 100;        % Distance between layers in meters

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

transmissionProbability = 0.3;      % Probability of data transmission per access node per time step

% Calculate propagation delay between layers

propagationDelay = distanceBetweenLayers / propagationSpeed;

% Initialize Transmission Log and Delays

totalNodes = numCoreNodes + numDistributionNodes + numAccessNodes;

transmissions = zeros(totalNodes, simulationTime); % Track transmissions per node

delays = zeros(totalNodes, simulationTime);        % Track delay per transmission

% Define Layer Ranges in Node Indexing

coreRange = 1:numCoreNodes;

distributionRange = (numCoreNodes + 1):(numCoreNodes + numDistributionNodes);

accessRange = (numCoreNodes + numDistributionNodes + 1):totalNodes;

% Simulate Data Transmission from Access Layer Upwards

for t = 1:simulationTime

% Randomly select access nodes to initiate data transmission

transmittingNodes = accessRange(rand(1, numAccessNodes) < transmissionProbability);

for node = transmittingNodes

% Select a random distribution node to forward data

distributionNode = distributionRange(randi(numDistributionNodes));

% Log transmission from access node to distribution node

transmissions(node, t) = 1; % Mark transmission at access node

transmissions(distributionNode, t + 1) = 1; % Transmission to distribution node in the next time step

delays(node, t) = propagationDelay; % Delay from access to distribution

% Select a random core node for final routing

coreNode = coreRange(randi(numCoreNodes));

% Log transmission from distribution node to core node

transmissions(coreNode, t + 2) = 1; % Transmission to core node after another time step

delays(distributionNode, t + 1) = propagationDelay; % Delay from distribution to core

disp([‘Time ‘ num2str(t) ‘s: Access Node ‘ num2str(node) ‘ sent data to Distribution Node ‘ num2str(distributionNode)]);

disp([‘Time ‘ num2str(t + 1) ‘s: Distribution Node ‘ num2str(distributionNode) ‘ sent data to Core Node ‘ num2str(coreNode)]);

end

end

% Visualize Transmission Activity Across Nodes in the Hierarchical Topology

time = 1:simulationTime;

% Plot Transmission Activity for Each Node

figure;

for node = 1:totalNodes

subplot(totalNodes, 1, node);

stem(time, transmissions(node, :), ‘filled’, ‘DisplayName’, [‘Node ‘ num2str(node)]);

if ismember(node, coreRange)

title([‘Core Node ‘ num2str(node) ‘ Transmission Activity’]);

elseif ismember(node, distributionRange)

title([‘Distribution Node ‘ num2str(node) ‘ Transmission Activity’]);

else

title([‘Access Node ‘ num2str(node) ‘ Transmission Activity’]);

end

xlabel(‘Time (s)’);

ylabel(‘Transmission (1 = Yes, 0 = No)’);

end

% Overview of Delays Across All Nodes

figure;

imagesc(delays);

colorbar;

title(‘Propagation Delay in Hierarchical Topology’);

xlabel(‘Time (s)’);

ylabel(‘Node ID’);

yticks(1:totalNodes);

yticklabels(arrayfun(@(x) [‘Node ‘ num2str(x)], 1:totalNodes, ‘UniformOutput’, false));

Explanation of the Code

  • Parameters:
    • numCoreNodes, numDistributionNodes, and numAccessNodes describe the number of nodes within each layer.
    • distanceBetweenLayers and propagationSpeed are utilized to compute the propagation delay among layers.
  • Transmission Simulation:
    • Access nodes need a probability of starting the data transmission each time step.
    • Data flows from an access node to a arbitrarily selected distribution node and then to a core node.
    • Each transmission is recorded, and a delay is logged for each layer-to-layer hop.
  • Propagation Delay Tracking:
    • The delays matrix logs delays for each transmission between nodes across layers.
  • Visualization:
    • The initial collection of plots indicates each node’s transmission activity over time, which arranged by layer.
    • The second plot is a heatmap that displaying propagation delays for each node, and offering an overview of the delay distribution within the topology.

Analysis and Extension Ideas

  • Bidirectional Data Flow: Change the code to enable the data transmission from core nodes down to access nodes.
  • Variable Delays: Set diverse distances among each layer to replicate the realistic delay variations within large networks.
  • Traffic Prioritization: Execute traffic prioritization in core or distribution nodes for particular data types.
  • Node Failure Simulation: Arbitrarily inactivate nodes replicating failures and learn resilience.
  • Dynamic Routing: Execute a routing protocol to discover best paths dynamically according to the traffic load.

These projects ideas help you to carry out the simulation of Hierarchical Topology Projects in MATLAB environment using provided simulation method. If you have any query on this topic, we will clear it.

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