To simulate Dynamic Source Routing (DSR) using MATLAB, we can make a design of an ad-hoc network in which nodes actively establish routes according to the route discovery and route maintenance processes. DSR is a reactive routing protocol utilized within mobile ad-hoc networks (MANETs) in which routes are made only when required. Every single packet carries the comprehensive path (source route) from the origin to the destination that creating it robust for dynamic topologies.
Following is a structured methodology to configuring a DSR simulation in MATLAB.
Steps to Simulate DSR in MATLAB
- Define Network Topology:
- We can utilize an adjacency matrix or graph object to denote the nodes and links in which each link has a weight signifying distance or cost.
- In a MANET, these links can modify actively to replicate mobility.
- Route Discovery Process:
- When a source node requires transmitting a packet to a destination then it introduce a route discovery by propagating a Route Request (RREQ).
- Nodes receiving the RREQ send it to its neighbors until the destination is attained whenever each node logs the route within the packet.
- Route Reply Process:
- The destination node transmits a Route Reply (RREP) packet again to the source, which following the reverse of the route discovered for the period of the RREQ phase.
- When the source receives the RREP then it saves the route within their cache.
- Simulate Packet Forwarding with Source Routing:
- Every single packet takes the whole route from the origin to the destination. Nodes send packets along this precomputed route.
- If a route is broken as a result of node mobility or failure then introduce a new route discovery.
- Visualize and Analyze Results:
- Design the network topology and emphasise paths carried by packets.
- Monitor parameters such as hop count, total path cost, and amount of control messages for route discovery.
Example Code Outline
Below is a MATLAB code framework to replicate the DSR with simple route discovery and packet forwarding.
% Define network topology as an adjacency matrix with link weights
adjMatrix = [
0 1 0 0 1;
1 0 1 1 0;
0 1 0 1 1;
0 1 1 0 0;
1 0 1 0 0
];
numNodes = size(adjMatrix, 1);
% Function to perform route discovery using depth-first search (DFS) to find all paths
function paths = findRoutes(adjMatrix, src, dest)
paths = {};
stack = {src}; % Stack to hold nodes for DFS
visited = false(1, size(adjMatrix, 1)); % Visited nodes
path = [];
function dfs(node)
visited(node) = true;
path = [path, node]; % Add node to current path
if node == dest
paths{end+1} = path; % Store path if destination is reached
else
neighbors = find(adjMatrix(node, 🙂 > 0);
for i = 1:length(neighbors)
if ~visited(neighbors(i))
dfs(neighbors(i));
end
end
end
path(end) = []; % Remove node from path (backtrack)
visited(node) = false;
end
dfs(src);
end
% Route discovery from source to destination
srcNode = 1; % Source node
destNode = 4; % Destination node
routes = findRoutes(adjMatrix, srcNode, destNode);
% Display all discovered routes from source to destination
disp([‘Discovered routes from node ‘, num2str(srcNode), ‘ to node ‘, num2str(destNode), ‘:’]);
for i = 1:length(routes)
disp([‘Route ‘, num2str(i), ‘: ‘, num2str(routes{i})]);
end
% Choose the first route as the selected route (simplified choice for this example)
selectedRoute = routes{1};
% Function to simulate packet forwarding using the selected route
function forwardPacket(route)
disp([‘Forwarding packet along route: ‘, num2str(route)]);
for i = 1:length(route)-1
disp([‘Packet forwarded from node ‘, num2str(route(i)), ‘ to node ‘, num2str(route(i+1))]);
end
disp([‘Packet delivered to destination node ‘, num2str(route(end))]);
end
% Forward packet using the selected route
disp(‘— Packet Transmission —‘);
forwardPacket(selectedRoute);
% Visualize the network topology
G = graph(adjMatrix);
figure;
plot(G, ‘EdgeLabel’, G.Edges.Weight);
title(‘Network Topology’);
Explanation of the Code
- Network Topology: The adjacency matrix adjMatrix signifies the network in which each non-zero entry denotes a link among the nodes.
- Route Discovery (DFS): The findRoutes function executes a depth-first search (DFS) from the origin to the destination, which discovering entire possible paths. In a real DSR protocol, just one path would be selected, and the source node could cache it.
- Route Selection: For simplicity, this instance utilizes the initial discovered route. DSR could normally select the shortest or best route according to the certain criteria.
- Packet Forwarding: The forwardPacket function replicates packet forwarding along the chosen route, including each intermediate node sending the packet to the next node within the path.
- Visualization: The network topology is showed using MATLAB’s graph and plot functions.
Visualization and Analysis
To examine and envision DSR routing:
- Network Visualization: Show the network topology and indicate the discovered route from origin to destination.
- Metrics Tracking: Record parameters like hop count, total path cost, and amount of control messages needed for route discovery.
Extending the Simulation
For a more complete DSR routing simulation:
- Route Maintenance: Execute the route error managing. If a route fails by reason of node movement then cause a new route discovery.
- Multiple Routes: Cache several routes from the source to the destination and execute the route selection rely on criteria such as hop count or reliability.
- Dynamic Network: Replicate node movement by actively modifying adjMatrix, which causing route discoveries and maintenance as required.
- Route Caching Optimization: Execute the route caching to minimize the amount of route discoveries. If they are still valid then the nodes can reuse routes.
With the help of this procedure you can obtain the knowledge for simulating and configuring Dynamic Source Routing (DSR) Routing projects and extending it using MATLAB environment. We are able to offer more detailed insights according to your needs. Send us all your research doubts to us , by dropping a mail we offer you good simulation support and project topics upon your needs.
