To simulate the Destination-Sequenced Distance Vector (DSDV) routing protocol using MATLAB that encompasses to design how DSDV functions in Mobile Ad-Hoc Networks (MANETs). DSDV is a proactive routing protocol in which each node sustains a routing table with routes to all other node within the network. It utilizes a distance-vector algorithm, which improved with series of numbers to prevent the routing loops and make sure the novelty of routes. Now, we follow the below steps to simulating DSDV protocol projects using MATLAB:
Steps to Simulate DSDV Protocol Projects in MATLAB
- Understanding DSDV
The DSDV protocol functions as follows:
- Routing Tables: All nodes sustain a table including the next hop to attain every other nodes and the amount of hops or distance.
- Sequence Numbers: Every single node route has a series of number showing the novelty of the route.
- Route Updates: Periodically, each node transmits their routing table to its neighbors. If a neighbor understands a shorter route or a route including a higher sequence number then it updates their routing table.
- Define the Network Topology
We must describe a network of mobile nodes (typically modeled as a graph) in which nodes are associated by wireless links. The graph nodes denote the mobile devices, and the edges signify wireless connections among them.
Example: Define a simple network topology with 5 nodes
% Define the nodes in the network
nodes = {‘Node1’, ‘Node2’, ‘Node3’, ‘Node4’, ‘Node5’};
% Define the connections (edges) between nodes (adjacency matrix)
connections = [0 1 1 0 0;
1 0 1 1 0;
1 1 0 1 1;
0 1 1 0 1;
0 0 1 1 0]; % Symmetric connectivity matrix
% Create a graph representing the network topology
G = graph(connections, nodes);
% Plot the network topology
figure;
plot(G, ‘Layout’, ‘force’);
title(‘DSDV Network Topology’);
- Initialize Routing Tables
In DSDV, every single node sustains a routing table along with entries for each destination, the next hop, and the hop count or distance. Also, the table involves series of numbers to make certain the route is update.
Example: Initialize the routing tables for each node
% Initialize routing tables for each node
routing_table = struct();
num_nodes = length(nodes);
% Set initial values for routing tables (infinity for unreachable nodes, 0 for self)
for i = 1:num_nodes
routing_table.(nodes{i}) = struct();
for j = 1:num_nodes
if i == j
routing_table.(nodes{i}).(nodes{j}) = struct(‘NextHop’, nodes{i}, ‘Distance’, 0, ‘SeqNum’, 0);
else
routing_table.(nodes{i}).(nodes{j}) = struct(‘NextHop’, ‘None’, ‘Distance’, inf, ‘SeqNum’, 0);
end
end
end
% Display initial routing table for a node (e.g., Node1)
disp(‘Initial Routing Table for Node1:’);
disp(routing_table.Node1);
- Simulate Route Updates
Every single node periodically transmits their routing table to its neighbors. Neighbors update its tables according to the received data that is select the route with the lower hop count or the higher sequence number.
Example: Broadcast route updates from Node1 to its neighbors
% Simulate route update broadcast from Node1 to its neighbors (Node2 and Node3)
neighbors = {‘Node2’, ‘Node3’}; % Neighbors of Node1
% Update the routing table of the neighbors based on Node1’s table
for i = 1:length(neighbors)
for j = 1:num_nodes
dest_node = nodes{j};
if routing_table.Node1.(dest_node).Distance + 1 < routing_table.(neighbors{i}).(dest_node).Distance
% Update route if a shorter path is found via Node1
routing_table.(neighbors{i}).(dest_node).NextHop = ‘Node1’;
routing_table.(neighbors{i}).(dest_node).Distance = routing_table.Node1.(dest_node).Distance + 1;
routing_table.(neighbors{i}).(dest_node).SeqNum = routing_table.Node1.(dest_node).SeqNum;
end
end
end
% Display the updated routing table for Node2
disp(‘Updated Routing Table for Node2 after receiving update from Node1:’);
disp(routing_table.Node2);
This procedure replicates how DSDV nodes up-to-date its routing tables after receiving routing data from their neighbors.
- Implement Route Advertisement
In DSDV, each node periodically transmits its routing table to their neighbors. We can replicate the periodic route advertisements and table updates.
Example: Periodic route advertisement and table update
% Define a function to perform a periodic route update
function routing_table = broadcast_route_update(source, neighbors, routing_table, nodes)
num_nodes = length(nodes);
% For each neighbor, update its routing table
for i = 1:length(neighbors)
for j = 1:num_nodes
dest_node = nodes{j};
if routing_table.(source).(dest_node).Distance + 1 < routing_table.(neighbors{i}).(dest_node).Distance
% Update the neighbor’s routing table if a shorter path is found
routing_table.(neighbors{i}).(dest_node).NextHop = source;
routing_table.(neighbors{i}).(dest_node).Distance = routing_table.(source).(dest_node).Distance + 1;
routing_table.(neighbors{i}).(dest_node).SeqNum = routing_table.(source).(dest_node).SeqNum;
end
end
end
end
% Simulate periodic route advertisements from Node1
routing_table = broadcast_route_update(‘Node1’, {‘Node2’, ‘Node3’}, routing_table, nodes);
% Display updated routing table for Node2
disp(‘Routing Table for Node2 after periodic update from Node1:’);
disp(routing_table.Node2);
We can utilize this function to mimic periodic updates from several nodes that leading to a completely updated routing table for each node.
- Simulate Node Movement and Link Breakages
In a MANET, nodes are moveable, and links among them, which can break by reason of mobility. DSDV manages the link breakages by publicizing endless distances for broken routes. We can replicate it by eliminating the connections amongst nodes.
Example: Simulate link breakage between Node1 and Node3
% Simulate the breakage of the link between Node1 and Node3
fprintf(‘Link between Node1 and Node3 is broken\n’);
% Update Node1’s table to advertise infinity distance for Node3
routing_table.Node1.Node3.Distance = inf;
routing_table.Node1.Node3.SeqNum = routing_table.Node1.Node3.SeqNum + 1; % Increment sequence number
% Broadcast the updated routing table from Node1
routing_table = broadcast_route_update(‘Node1’, {‘Node2’}, routing_table, nodes);
% Display the updated routing table for Node2 after the link break
disp(‘Routing Table for Node2 after link break between Node1 and Node3:’);
disp(routing_table.Node2);
This replicates how DSDV manages the link failures by marking routes as inaccessible (setting distance to infinity) and transmitting the updated routing data.
- Evaluate Protocol Performance
After replicating the DSDV’s operation, we can estimate its performance such as:
- Convergence Time: How rapidly the routing tables meet to reflect exact routes.
- Packet Delivery Ratio: The ratio of effectively delivered packets to total transmitted packets.
- Routing Overhead: The number of control information (routing updates) are swapped among nodes.
Monitoring the number of routing updates is exchanged and the amount of effectively delivered packets, expand the simulation to compute these parameters.
Example Project Ideas for DSDV Simulation in MATLAB
- DSDV Performance in Dynamic Networks: Replicate a MANET with moving nodes and assess how rapidly DSDV adjusts to topology changes, like node movement and link breakages. Estimate the convergence time and packet delivery ratio.
- Energy-Efficient DSDV Routing: Mimic an energy-aware version of DSDV in which nodes deliberate the battery levels once selecting routes. Examine how it influences the lifetime of the network and routing efficiency.
- Scalability of DSDV in Large MANETs: Replicate a large-scale network along with multiple nodes and then estimate the routing overhead, convergence time, and scalability of DSDV within a highly dynamic environment.
- Comparison of Proactive and Reactive Protocols: Liken the performance of DSDV (proactive) including reactive protocols such as AODV or DSR like packet delivery ratio, routing overhead, and delay in both static and dynamic situations.
- Security in DSDV: Execute the security enhancements in DSDV, like securing route advertisements versus malicious nodes, and investigate how these improvements impact the protocol performance.
Tools for DSDV Simulation in MATLAB
- Graph Theory Toolbox: It is very helpful for designing the network as a graph and replicating route updates and modifications within network topology.
- Statistics and Machine Learning Toolbox: It can be utilized to investigate the protocol performance and mimic mobility patterns in MANETs.
- MATLAB File Exchange: Discover the resources shared by the MATLAB community for mobility models, routing algorithms, and network simulations.
The MALAB environment enabled to perform the simulation process that containing key concepts with sample coding, example projects ideas and tools for simulating the Destination-Sequenced Distance Vector (DSDV). We’re able to share more updated information related to this projects, if necessary.
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