How to Implement Bellman Ford Routing in NS2
To implement the Bellman-Ford algorithm in ns2, it is also called distance-vector routing protocol which is used in dynamic routing, where each node upholds a distance vector table that has the shortest distance (depends on hop count or cost) to every other node in the network. The Bellman-Ford algorithm is especially helpful because it can handle graphs with negative edge weights and can detect negative cycles.
Execute the custom routing agent or utilize the available distance vector-based protocols like DV (Distance Vector) routing protocol to simulate the Bellman Ford algorithm in ns2 by altering the distance vector protocol and how it repeatedly updates routing tables.
While NS2 does not have an obvious Bellman-Ford implementation, the DV routing protocol imitates the activities of the Bellman-Ford algorithm. Keep in contact with us; we are prepared to provide you with the best implementation support on Bellman-Ford algorithm.
Below is a step-by-step guide to simulating Bellman-Ford-like behavior in NS2.
Steps to Implement Bellman-Ford in NS2
- Set Up NS2 Environment
- Make certain that NS2 is installed and configured correctly on your system.
- Understand Bellman-Ford Routing
- In Bellman-Ford, each node upholds a distance vector (a table of distances to other nodes).
- The node updates its distance vector by interchanging information with its neighbors. The update rule is: Dxy=min(Dxy,Dxz+Dzy)D_{xy} = \min(D_{xy}, D_{xz} + D_{zy})Dxy=min(Dxy,Dxz+Dzy) where DxyD_{xy}Dxy is the distance from node xxx to node yyy, and zzz is a neighboring node.
- Simulate Bellman-Ford with Distance Vector (DV) Routing
NS2 offers a DV (Distance Vector) protocol that functions likewise the Bellman-Ford algorithm. We’ll use this to explain the Bellman-Ford-like behavior.
Example OTcl Script for Bellman-Ford (Distance Vector) in NS2
# Define the simulation environment
set ns [new Simulator]
# Open the trace file for recording data
set tracefile [open out.tr w]
$ns trace-all $tracefile
# Define the finish procedure
proc finish {} {
global ns tracefile
$ns flush-trace
close $tracefile
exec nam out.nam &
exit 0
}
# Create network nodes
set node1 [$ns node]
set node2 [$ns node]
set node3 [$ns node]
set node4 [$ns node]
set node5 [$ns node]
# Create duplex links between nodes with different delays and bandwidths
$ns duplex-link $node1 $node2 10Mb 10ms DropTail
$ns duplex-link $node2 $node3 10Mb 10ms DropTail
$ns duplex-link $node3 $node4 10Mb 10ms DropTail
$ns duplex-link $node4 $node5 10Mb 10ms DropTail
$ns duplex-link $node1 $node5 5Mb 50ms DropTail
$ns duplex-link $node2 $node4 5Mb 30ms DropTail
# Enable dynamic routing protocol (Distance Vector – DV)
$ns rtproto DV
# Attach TCP agents for traffic generation
set tcp [new Agent/TCP]
$ns attach-agent $node1 $tcp
set sink [new Agent/TCPSink]
$ns attach-agent $node5 $sink
# Connect the TCP agent and sink
$ns connect $tcp $sink
# Create an FTP application and attach it to TCP
set ftp [new Application/FTP]
$ftp attach-agent $tcp
# Start the FTP application at 1 second
$ns at 1.0 “$ftp start”
# Simulate link failure between node2 and node3 at time 3.0 seconds
$ns rtmodel-at 3.0 down $node2 $node3
# Restore the link between node2 and node3 at time 6.0 seconds
$ns rtmodel-at 6.0 up $node2 $node3
# Stop the simulation at 10.0 seconds
$ns at 10.0 “finish”
# Run the simulation
$ns run
Explanation of the Script:
- Network Topology: The script states a network with five nodes, each linked by duplex links with various bandwidths and delays.
- Distance Vector Protocol (DV): The line $ns rtproto DV enables NS2’s built-in distance vector routing protocol, which acts in the same way as the Bellman-Ford algorithm by interchanging routing information amongst neighbors and updating routing tables in terms of shortest path calculation.
- Traffic Generation: TCP traffic is developed amidst node1 (source) and node5 (destination) using an FTP application to replicate data transfer.
- Link Failure and Recovery: At time 3 seconds, the link amongst node2 and node3 fails. The DV protocol tunes to this failure by recalculating routes. The link is restored at 6 seconds, and the routing tables are updated again to reflect the new network state.
- Simulation Duration: The simulation executes for 10 seconds.
Running the Simulation
- Save the script as bellman_ford_routing.tcl.
- Execute the script in NS2:
ns bellman_ford_routing.tcl
- The simulation will produce a trace file (out.tr) and a Network Animator (NAM) file (out.nam). Visualize the simulation and monitor how routes are updated after the link failure and recovery by using NAM.
Analyze the Results
- Trace File: The trace file has detailed information about packet transmissions, delays, and route varies. Evaluate the trace files and verify that the routing tables were updated properly based on the Bellman-Ford algorithm by using tools like grep or awk.
- NAM Visualization: Use NAM to assess how packets are forwarded amongst nodes. You should see how the DV protocol adjusts to the link failure by updating routes and redirecting traffic.
Enhancements
- Custom Link Costs: You can fine-tune the link costs to replicate various network conditions and monitor how the Bellman-Ford algorithm updates the routes.
- Additional Traffic Flows: Simulate more modern networks by attaching more traffic flows amongst various node and see how the routing tables are updated in reaction to several routes.
- Longer Simulation Time: Expand the simulation time and launch more dynamic network changes like additional link failures, jamming, or node mobility.
- Negative Edge Weights: To fully replicate Bellman-Ford’s ability to manage negative edge weights, you can experiment by manually modifying link costs to negative values (though this requires careful handling in NS2, as negative weights might not be directly supported by default).
In this step-by-step technique, we have given the information that helps you when implementing Bellman Ford Routing Algorithm using ns2 simulation tool including sample snippet codes. You can include the modern mechanisms for future enhancement purpose.