To simulate dynamic routing using MATLAB which encompasses constantly updating the routing tables depends on present network conditions like link costs and node availability. In MATLAB, we need to replicate a dynamic routing protocol by enabling the network conditions to modify over time that prompting each node to modernize their routing table dynamically utilizing a shortest path algorithm such as Dijkstra’s algorithm.
Given is a step-by-step method for simulating a Dynamic Routing Protocol in MATLAB.
Steps to Simulate Dynamic Routing in MATLAB
- Define the Initial Network Topology and Parameters:
- Denote the network in which each entry shows the cost amongst nodes using an adjacency matrix.
- Describe a time series of modifications in link costs to replicate the dynamic network conditions.
% Define number of nodes
numNodes = 6;
infCost = inf; % Define infinity cost for no direct connection
% Initial adjacency matrix with link costs
linkCosts = [0 1 infCost infCost infCost infCost;
1 0 4 2 infCost infCost;
infCost 4 0 3 infCost infCost;
infCost 2 3 0 2 3;
infCost infCost infCost 2 0 4;
infCost infCost infCost 3 4 0];
% Time series of link changes to simulate network dynamics
dynamicChanges = {
3, 2, infCost; % Set link between nodes 3 and 2 to infinity at time step 3
5, 4, 1; % Change link cost between nodes 5 and 4 to 1 at time step 5
6, 3, infCost; % Set link between nodes 6 and 3 to infinity at time step 6
2, 4, 5; % Change link cost between nodes 2 and 4 to 5 at time step 8
};
- Implement Dijkstra’s Algorithm for Shortest Path Calculation:
- Every single node executes the Dijkstra’s algorithm to update their routing table according to the recent state of the link costs.
- This function will be requested every time a change is identified within the network.
function [distances, previous] = dijkstra(linkCosts, sourceNode)
numNodes = size(linkCosts, 1);
distances = inf(1, numNodes); % Initialize distances to infinity
distances(sourceNode) = 0; % Distance to itself is 0
previous = zeros(1, numNodes); % Previous nodes for path reconstruction
visited = false(1, numNodes); % Track visited nodes
for i = 1:numNodes
% Find the unvisited node with the smallest distance
[~, u] = min(distances + inf * visited); % Exclude visited nodes
visited(u) = true;
% Update distances for neighboring nodes
for v = 1:numNodes
if ~visited(v) && linkCosts(u, v) < inf
newDist = distances(u) + linkCosts(u, v);
if newDist < distances(v)
distances(v) = newDist;
previous(v) = u;
end
end
end
end
end
- Simulate the Dynamic Routing Algorithm with Time Steps:
- At each time step, verify if there are alters within the link costs.
- If modifications happen then we update the link costs and recompute the routing tables for each node.
maxTimeSteps = 10; % Define the number of time steps for the simulation
% Simulation loop for dynamic routing
for t = 1:maxTimeSteps
disp([‘Time Step: ‘, num2str(t)]);
% Apply any changes in link costs for the current time step
for change = 1:size(dynamicChanges, 1)
if dynamicChanges{change, 1} == t
node1 = dynamicChanges{change, 2};
node2 = dynamicChanges{change, 3};
newCost = dynamicChanges{change, 4};
linkCosts(node1, node2) = newCost;
linkCosts(node2, node1) = newCost;
disp([‘Updated link cost between Node ‘, num2str(node1), ‘ and Node ‘, num2str(node2), ‘ to ‘, num2str(newCost)]);
end
end
% Recalculate shortest paths for each node
for node = 1:numNodes
[distances, previous] = dijkstra(linkCosts, node);
disp([‘Routing table for Node ‘, num2str(node), ‘ at time step ‘, num2str(t)]);
for dest = 1:numNodes
if node ~= dest
% Reconstruct the path from source to destination
path = dest;
while previous(path(1)) > 0
path = [previous(path(1)), path];
end
disp([‘Destination ‘, num2str(dest), ‘: Path ‘, num2str(path), ‘, Cost ‘, num2str(distances(dest))]);
end
end
disp(‘————————–‘);
end
disp(‘==========================’);
end
- Visualize the Network Topology and Changes Over Time (Optional):
- Envision the network using MATLAB plotting functions, which indicating link costs and modifications as they occur.
% Define node positions for visualization
nodePositions = [10 10; 20 10; 20 20; 10 20; 15 25; 25 20];
% Function to plot the network with current link costs
function plotNetwork(linkCosts, nodePositions, numNodes)
clf;
hold on;
for i = 1:numNodes
for j = i+1:numNodes
if linkCosts(i, j) < inf
plot([nodePositions(i, 1), nodePositions(j, 1)], …
[nodePositions(i, 2), nodePositions(j, 2)], ‘k–‘);
midPoint = (nodePositions(i, 🙂 + nodePositions(j, :)) / 2;
text(midPoint(1), midPoint(2), num2str(linkCosts(i, j)), …
‘HorizontalAlignment’, ‘center’, ‘BackgroundColor’, ‘white’);
end
end
plot(nodePositions(i, 1), nodePositions(i, 2), ‘bo’); % Plot nodes
text(nodePositions(i, 1), nodePositions(i, 2), num2str(i), …
‘VerticalAlignment’, ‘bottom’, ‘HorizontalAlignment’, ‘center’);
end
title(‘Dynamic Network Topology with Link Costs’);
hold off;
end
% Call plotNetwork function after each time step in the simulation loop
plotNetwork(linkCosts, nodePositions, numNodes);
pause(1); % Pause for 1 second to visualize each step
- Analyze Routing Table Updates and Path Efficiency (Optional):
- Observe the amount of updates to each routing table and the path cost for each route over time.
- Monitor how the dynamic modifications impact the paths are chosen by each node.
% Example analysis: Collect path costs for each time step
pathCostsOverTime = zeros(numNodes, maxTimeSteps);
for t = 1:maxTimeSteps
for node = 1:numNodes
[distances, ~] = dijkstra(linkCosts, node);
pathCostsOverTime(node, t) = sum(distances(~isinf(distances)));
end
end
disp(‘Total path costs for each node over time:’);
disp(pathCostsOverTime);
Explanation of Key Components
- Dynamic Link Costs: The simulation implement modifications to link costs at specified time steps that permitting for network conditions to progress over time.
- Dijkstra’s Algorithm: Each node executes the Dijkstra’s algorithm to modernize their routing table depends on current link costs, which making sure that it adjusts to the network changes.
- Path Reconstruction: After computing the distances, paths from each node to all other nodes are rebuilt that offering a complete view of the routing tables.
- Visualization: The network topology and link costs are envisioned which enabling observation of the effect of modifications on the routing decisions.
Possible Extensions
- Add Failure Recovery: Replicate the node or link failures, and then monitor how nodes reroute all over the broken links.
- Dynamic Load Balancing: Launch traffic demand on each link and change link costs relies on congestion levels to mimic load-aware routing.
- Adaptive Algorithms: Manage dynamic changes and liken performance using alternative routing algorithms or enhancements such as Bellman-Ford.
With the help of MATLAB, we thoroughly simulated and analysed the Dynamic Routing projects using the above basic simulation approach and we are prepared to offer more complete exploration of this topic.
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