How to Simulate EIGRP Protocol Projects Using MATLAB

To simulate an Enhanced Interior Gateway Routing Protocol (EIGRP) using MATLAB, it is an advanced distance-vector routing protocol utilized mainly in Cisco networks. It is modeled to offer efficient routing along with faster convergence, less bandwidth usage, and better performance likened to traditional distance-vector protocols. EIGRP utilizes a permutation of the distance vector and link-state properties, and its main modules contain dual finite state machine (DUAL), neighbor discovery, and reliable transport.

We will instruct you on how to simulate EIGRP protocol projects using MATLAB:

Steps to Simulate EIGRP Protocol Projects in MATLAB

1. Understand EIGRP Components

It is a crucial to know its key aspects, before replicating EIGRP:

• Neighbor Discovery: Routers find out and sustain neighbors with periodic hello messages.
• Topology Table: Stores data regarding every route known to the router.
• DUAL Algorithm: Makes sure loop-free, rapid convergence. Routes are noticed as either a successor (best path) or a feasible successor (backup path).
• Metrics: EIGRP utilizes a composite parameters according to the bandwidth, delay, reliability, load, and MTU.

2. Define Network Topology

The initial stage in the simulation is describing the network topology of routers. We can design the routers as nodes and the connections as edges amongst the nodes. Every single edge can have properties such as bandwidth, delay, and so on, that will be utilized within EIGRP metric calculation.

Example: Define a simple network with 4 routers

% Define routers as nodes

routers = {‘R1’, ‘R2’, ‘R3’, ‘R4’};

% Define the connections (edges) between routers (adjacency matrix)

% Each connection has a bandwidth (in Mbps) and delay (in ms)

connections = [

0 100 10 0;  % R1 connected to R2 with 100 Mbps and 10 ms delay

100 0 50 20; % R2 connected to R3 with 50 Mbps and 20 ms delay

10 50 0 30;  % R3 connected to R4 with 50 Mbps and 30 ms delay

0 20 30 0    % R4 connected to R2 and R3

];

% Create a graph representing the network topology

G = graph(connections, routers);

% Plot the network topology

figure;

plot(G, ‘EdgeLabel’, G.Edges.Weight);

title(‘EIGRP Network Topology’);

3. Metric Calculation for EIGRP

EIGRP computes the metric rely on bandwidth and delay. The formula is:

Metric=(107Minimum Bandwidth+Cumulative Delay)×256\text{Metric} = \left( \frac{10^7}{\text{Minimum Bandwidth}} + \text{Cumulative Delay} \right) \times 256Metric=(Minimum Bandwidth107​+Cumulative Delay)×256

• Bandwidth is the minimum bandwidth along the path (in Kbps).
• Delay is the total of delays along the path (in microseconds).

Example: Implement EIGRP metric calculation

% Define the bandwidth (in Kbps) and delay (in microseconds) for each link

link_bandwidths = [100000, 50000, 10000, 20000]; % Bandwidth in Kbps

link_delays = [10000, 20000, 30000, 15000]; % Delay in microseconds

% Calculate the EIGRP metric for each link

eigrp_metric = @(bw, delay) ((10^7 ./ bw) + delay) * 256;

% Compute metrics for each link

metrics = eigrp_metric(link_bandwidths, link_delays);

% Display the computed EIGRP metrics

fprintf(‘EIGRP Metrics for each link:\n’);

for i = 1:length(metrics)

fprintf(‘Link %d: %.2f\n’, i, metrics(i));

end

This example computes the EIGRP metric depends on bandwidth and delay for every single link within the network.

4. EIGRP Neighbor Discovery

EIGRP routers utilize the hello messages to determine and sustain neighbor relationships. We can replicate the periodic hello messages among the routers, and establish neighbor relationships according to the reachability.

Example: Simulate neighbor discovery

% Define neighbors for each router

neighbors = containers.Map;

neighbors(‘R1’) = {‘R2’, ‘R3’};

neighbors(‘R2’) = {‘R1’, ‘R3’, ‘R4’};

neighbors(‘R3’) = {‘R1’, ‘R2’, ‘R4’};

neighbors(‘R4’) = {‘R2’, ‘R3’};

% Simulate periodic hello message exchanges

fprintf(‘Simulating EIGRP Neighbor Discovery:\n’);

for i = 1:length(routers)

fprintf(‘%s sends hello messages to: %s\n’, routers{i}, strjoin(neighbors(routers{i}), ‘, ‘));

end

In this code snippets, routers swap hello messages to find their neighbors and create communication links.

5. EIGRP Topology Table and DUAL Algorithm

Each router sustains a topology table, which stores every route studied from neighbors. Routes with the optimal parameters are noticed as successors, and backup routes are marked as possible successors.

We can replicate the process of constructing the topology table and choosing the optimal route utilizing the DUAL algorithm.

Example: Build a topology table and select successors

% Initialize the topology table for a router (e.g., R1)

topology_table = struct();

% Define routes learned from neighbors (each route has a destination, next hop, and metric)

topology_table.R1 = [

struct(‘Destination’, ‘R2’, ‘NextHop’, ‘R2’, ‘Metric’, eigrp_metric(100000, 10000)), % Route via R2

struct(‘Destination’, ‘R3’, ‘NextHop’, ‘R3’, ‘Metric’, eigrp_metric(50000, 20000))  % Route via R3

];

% Select the successor (best route) based on the lowest metric

[~, idx] = min([topology_table.R1.Metric]);

successor = topology_table.R1(idx);

% Display the selected successor route

fprintf(‘Successor route from R1 to %s via %s with metric %.2f\n’, successor.Destination, successor.NextHop, successor.Metric);

In this instance, we replicate how EIGRP chooses the finest path (successor) according to the metric.

6. Simulate EIGRP Route Propagation

When a router chooses the optimal route then it advertises this route to their neighbors. We can mimic route propagation via the network along with each router updating its routing table according to the received updates.

Example: Simulate route propagation

% Simulate route propagation from R1 to R2 and R3

fprintf(‘R1 advertises its route to R2 and R3\n’);

% R2 and R3 receive the update and update their topology tables

topology_table.R2 = [

struct(‘Destination’, ‘R1’, ‘NextHop’, ‘R1’, ‘Metric’, eigrp_metric(100000, 10000)),

struct(‘Destination’, ‘R3’, ‘NextHop’, ‘R3’, ‘Metric’, eigrp_metric(20000, 15000))

];

topology_table.R3 = [

struct(‘Destination’, ‘R1’, ‘NextHop’, ‘R1’, ‘Metric’, eigrp_metric(50000, 20000)),

struct(‘Destination’, ‘R4’, ‘NextHop’, ‘R4’, ‘Metric’, eigrp_metric(30000, 20000))

];

% Display updated topology tables for R2 and R3

disp(‘Updated Topology Table for R2:’);

disp(topology_table.R2);

disp(‘Updated Topology Table for R3:’);

disp(topology_table.R3);

In this replication, R1 advertises its route, and R2 and R3 update its topology tables consequently.

7. Simulate EIGRP Convergence and Failover

One of EIGRP’s benefits is their rapid convergence and capacity to manage the failover situations utilizing feasible successors. We can replicate a link failure and experiment how EIGRP meets to a new route.

Example: Simulate a link failure and failover to feasible successor

% Simulate link failure between R1 and R2

fprintf(‘Link between R1 and R2 fails\n’);

topology_table.R1(1).Metric = inf;  % Mark the route as unreachable

% R1 switches to feasible successor (route via R3)

[~, idx] = min([topology_table.R1.Metric]);

feasible_successor = topology_table.R1(idx);

% Display the new selected route

fprintf(‘R1 switches to feasible successor: Route to %s via %s with metric %.2f\n’, feasible_successor.Destination, feasible_successor.NextHop, feasible_successor.Metric);

This simulates a link failure and how EIGRP quickly switches to an alternate route (feasible successor) to maintain connectivity.

8. Performance Evaluation

After replicating the EIGRP routing process, we can estimate its performance rely on:

• Convergence time: Compute how rapid the network converges after a topology modify.
• Routing overhead: Calculate the amount of route updates exchanged among the routers.
• Packet delivery ratio: Replicate the packet forwarding and estimate the ratio of effectively delivered packets.

Example Project Ideas for EIGRP Simulation in MATLAB

1. EIGRP vs OSPF Performance Comparison: Replicate and compare EIGRP with OSPF such as convergence time, routing overhead, and scalability within large networks.
2. Energy-Aware EIGRP Routing: Alter the EIGRP metric computation to integrate the node energy levels and then mimic the influence of energy-aware routing on network lifetime.
3. EIGRP Failover and Recovery Analysis: Replicate several link failures and examine how rapidly EIGRP switches to feasible successors and retrieves from network failures.
4. EIGRP in Hybrid Networks (Wired and Wireless): Mimic EIGRP within a mixed wired and wireless network and investigate its performance under diverse mobility and load conditions.
5. Security Enhancements in EIGRP: Execute and replicate the security mechanisms such as authentication or encryption within EIGRP and assess how they impact protocol performance.

Tools and Libraries for EIGRP Simulation in MATLAB

• Graph Theory Toolbox: It is helpful for signifying the network as a graph and replicating the route propagation and link failures.
• Communications Toolbox: It can support replicate the network communication and calculate routing protocol performance.
• MATLAB File Exchange: Discover tools and functions are distributed by the community for routing protocol simulation.

Through MATLAB based simulations, we had showed a detailed approach on how to replicate the EIGRP protocol projects and how to evaluate its performance in this manual. We are ready to extend the results with extra data if required.

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