How to Start Flooding Routing Projects Using MATLAB

To create a Flooding Routing project in MATLAB, we require replicating the process for a flooding-based routing protocol, in which the packets are broadcast to all reachable nodes in the network. Flooding is a simple, nevertheless for inefficient, methods to routing. It doesn’t need a complex approach such as link-state or distance-vector protocols, and it operates through replicating and transmitting the packets to all neighbours, except the one from which the packet was received.

Steps to start flooding routing projects Using MATLAB

Key Concepts of Flooding Routing

  • Flooding has including the transmitting the packet for all adjacent nodes such as neighbours and allowing the neighbours forward up until the destination is reached.
  • Duplicate Suppression: we prevent the infinite loops or unnecessary re communicate, the node must follow that the packets it has previously transmitted.
  • Hop Limit: We avoid the infinite transmit, a hop detect can be setting, then that are packet is discarded.

Steps to Implement Flooding Routing in MATLAB

  1. Define the Network Topology
    in flooding, we require to describe the network that each node can send packets to its neighbours. This can be signifies the adjacency matrix or adjacency list, in which every node such as router recognize its directly connected neighbours.

Adjacency Matrix Representation:

    • The matrix will hold 1 for a connection among the nodes and 0 for no connection.
    • The matrix is uncorrected, such as if a node i is connected to node j, both adjMatrix(i, j) and adjMatrix(j, i) will be 1.

Example:

% Define an adjacency matrix where 1 means there is a link between nodes

% 1: Node 1, 2: Node 2, 3: Node 3, etc.

adjMatrix = [

0, 1, 1, 0;  % Node 1 is connected to nodes 2 and 3

1, 0, 1, 0;  % Node 2 is connected to nodes 1 and 3

1, 1, 0, 1;  % Node 3 is connected to nodes 1, 2, and 4

0, 0, 1, 0   % Node 4 is connected to node 3

];

  1. Define Flooding Function Apply a function which replicates the flooding of a packet from a source node to other nodes in the network. The performance will be a:
    • Transmit the packet to all adjacent nodes.
    • Follow the visited nodes we prevent the processing for similar packet several times.
    • Alternatively, find the number of hops we avoid the packet from circulating endlessly.

Flooding Function:

function floodedNodes = floodPacket(adjMatrix, sourceNode, maxHops)

% adjMatrix: The adjacency matrix representing the network

% sourceNode: The node where the flooding starts

% maxHops: The maximum number of hops allowed before dropping the packet

n = size(adjMatrix, 1);   % Number of nodes in the network

visited = false(1, n);     % Keep track of visited nodes

visited(sourceNode) = true; % Mark the source node as visited

% Queue for nodes to process

toVisit = sourceNode;

hops = 0;                  % Track the number of hops

% Store the flooded nodes

floodedNodes = sourceNode;

while ~isempty(toVisit) && hops < maxHops

currentNode = toVisit(1); % Get the current node to process

toVisit(1) = [];          % Remove it from the queue

% Get the neighbors of the current node

neighbors = find(adjMatrix(currentNode, 🙂 == 1);

% Flood the packet to the neighbors

for i = 1:length(neighbors)

neighbor = neighbors(i);

if ~visited(neighbor)

visited(neighbor) = true; % Mark neighbor as visited

floodedNodes = [floodedNodes, neighbor]; % Add to flooded nodes

toVisit = [toVisit, neighbor]; % Add neighbor to the queue

end

end

hops = hops + 1;  % Increment hop count

end

end

Explanation of Flooding Function:

    • The function initialize through marking the sourceNode as visited.
    • It then uses for a queue such as toVisit to keep monitor of that nodes require to be processed.
    • Intended for each node, it detects the neighbours such as nodes connected directly to it, and if a neighbor hasn’t been visited, it improves the neighbor to the queue and marks it as visited.
    • This process frequently until all nodes are flooded or the hop limit for sample maxHops is reached.
  2. Simulate Flooding Routing Now; we can replicate the flooding process through calling the floodPacket function. For sample, if the flooding starts at node 1:

sourceNode = 1;     % Starting node for flooding (1-based index)

maxHops = 3;        % Maximum number of hops

floodedNodes = floodPacket(adjMatrix, sourceNode, maxHops);

disp(‘Flooded nodes:’);

disp(floodedNodes);

This will view for the nodes that received the packet during the flooding process, up to the maximum number of hops.

  1. Visualize the Network Topology Envision the network topology can supports you understand the connections on how the flooding propagates. We can use MATLAB’s graph or digraph to mark the network.

Example Visualization:

G = graph(adjMatrix);       % Create a graph object from the adjacency matrix

plot(G, ‘EdgeLabel’, G.Edges.Weight);  % Plot the graph with edge weights

  1. Simulate Dynamic Changes (Optional) We can replicate the dynamic variations in the network:
    • Link Failures: Eliminate the edges from the adjacency matrix we replicate the function failures.
    • Node Failures: Delete a row and column in the adjacency matrix and we replicate a node failure.

Example: Simulating a Link Failure such as removing a link between node 1 and node 2:

adjMatrix(1, 2) = 0;

adjMatrix(2, 1) = 0;

Next alter the network, we can reprocess for the floodPacket function to view on how the flooding is impacted.

  1. Handle Packet Duplication (Optional) we prevent the environment in which a node sending the similar packet several times such as which can lead to inefficiency and loops), you can implement a packet ID system. Every packet could have a unique ID, and nodes will keep monitor of that packet IDs they have previously processed.
  2. Testing and Debugging
    • Test with different topologies: Research through different network settings, such as fully connected, linearly connected, and ring topologies.
    • Change hop limits: Try different hop findings and examine on how the the network behaves in larger or further complex networks.
    • Monitor Performance: Flooding can be lead the network inefficiency, so validate the performance through following on how number of hops, packet duplication, and flooding time increases by network size.

Example of Complete MATLAB Code:

% Define the adjacency matrix for the network

adjMatrix = [

0, 1, 1, 0;  % Node 1 connected to nodes 2 and 3

1, 0, 1, 0;  % Node 2 connected to nodes 1 and 3

1, 1, 0, 1;  % Node 3 connected to nodes 1, 2, and 4

0, 0, 1, 0   % Node 4 connected to node 3

];

% Flooding function

function floodedNodes = floodPacket(adjMatrix, sourceNode, maxHops)

n = size(adjMatrix, 1);

visited = false(1, n);

visited(sourceNode) = true;

toVisit = sourceNode;

hops = 0;

floodedNodes = sourceNode;

while ~isempty(toVisit) && hops < maxHops

currentNode = toVisit(1);

toVisit(1) = [];

neighbors = find(adjMatrix(currentNode, 🙂 == 1);

for i = 1:length(neighbors)

neighbor = neighbors(i);

if ~visited(neighbor)

visited(neighbor) = true;

floodedNodes = [floodedNodes, neighbor];

toVisit = [toVisit, neighbor];

end

end

hops = hops + 1;

end

end

% Simulate flooding from node 1 with a hop limit of 3

sourceNode = 1;

maxHops = 3;

floodedNodes = floodPacket(adjMatrix, sourceNode, maxHops);

disp(‘Flooded nodes:’);

disp(floodedNodes);

Conclusion

Flooding routing is a straightforward protocol we apply in the MATLAB. We can easily represent the network topology using an adjacency matrix and replicate the flooding process through forwarding packets to neighbours. The key variations are handling the packet duplication, enable a limited number of hops, and avoid the unnecessary network load. Once we have the basic flooding functionality, you can extend it to replicate more complex environments such as network failures or performance analysis. We also offer more data how it performs in other simulation tools.