@harsh star Design a network topology using tcl code in ns2, that should contain at least one intermediate node. Use both TCP and UDP protocols with FTP and CBR traffic generated, respectively. Make sure that there is a congested link (bottleneck link). analyze the trace file generated using python code and compute the following:
• Calculate the total throughput of that link, with respect to time.
• Calculate the throughput of that link with respect to time, only for TCP packets.
• Calculate the throughput of that link with respect to time, only for UDP
packets.
#ns2
vagrant iron
harsh starBOT
<@1082069574901563453> Design a network topology using tcl code in ns2, that sho...
Creating a network topology in NS-2 (Network Simulator 2) and analyzing the generated trace file with Python requires a two-fold approach. First, we'll script the network topology using Tcl (Tool Command Language) for NS-2, and then, we'll write Python code to analyze the trace file generated by NS-2.
1. Designing Network Topology in NS-2
This NS-2 script sets up a simple network topology with one intermediate node, creating a bottleneck, and uses both TCP and UDP protocols for transmitting FTP and CBR (Constant Bit Rate) traffic, respectively.
# Create a simulator instance
set ns [new Simulator]
# Set up a file for the trace output
set tracefile [open simple.tr w]
$ns trace-all $tracefile
# Define a procedure to finish the simulation
proc finish {} {
global ns tracefile
$ns flush-trace
close $tracefile
exit 0
}
# Create nodes
set n0 [$ns node]
set n1 [$ns node]
set n2 [$ns node]
# Create links
$ns duplex-link $n0 $n1 1.5Mb 10ms DropTail
$ns duplex-link $n1 $n2 1Mb 20ms DropTail # Bottleneck link
$ns duplex-link-op $n1 $n2 queue-limit 10 # Creating congestion
# Create a UDP agent and attach it to node n0
set udp [new Agent/UDP]
$ns attach-agent $n0 $udp
set cbr [new Application/Traffic/CBR]
$cbr set packetSize_ 1000
$cbr set interval_ 0.005
$cbr attach-agent $udp
# Create a TCP agent and attach it to node n0
set tcp [new Agent/TCP]
$ns attach-agent $n0 $tcp
set ftp [new Application/FTP]
$ftp attach-agent $tcp
# Create sink agents for TCP and UDP at n2
set sink_udp [new Agent/Null]
$ns attach-agent $n2 $sink_udp
$ns connect $udp $sink_udp
set sink_tcp [new Agent/TCPSink]
$ns attach-agent $n2 $sink_tcp
$ns connect $tcp $sink_tcp
# Schedule events
$ns at 0.5 "$cbr start"
$ns at 1.0 "$ftp start"
$ns at 4.5 "finish"
# Run the simulation
$ns run
Save this script as network.tcl and run it with NS-2. The script will generate a trace file titled simple.tr, which contains detailed information about the simulation, including eve
harsh starBOT
Creating a network topology in NS-2 (Network Simulator 2) and analyzing the gene...
ry packet transmitted and received in the network.
2. Analyzing the Trace File with Python
Next, you'll use Python to analyze simple.tr, focusing on total throughput, and throughput for TCP and UDP packets.
import pandas as pd
# Load the trace file
columns = ['event', 'time', 'from_node', 'to_node', 'pkt_type', 'pkt_size', 'flags', 'flow_id', 'src_addr', 'dst_addr', 'seq_num', 'pkt_id']
df = pd.read_csv('simple.tr', sep=' ', names=columns)
# Filter packets that are received; r in the event column signifies that
df_received = df[df['event'] == 'r']
# Calculate total throughput
total_throughput = df_received['pkt_size'].sum() / df_received['time'].max()
print(f"Total throughput: {total_throughput} bytes/s")
# Calculate throughput for TCP packets only
tcp_throughput = df_received[df_received['pkt_type'] == 'tcp']['pkt_size'].sum() / df_received['time'].max()
print(f"TCP throughput: {tcp_throughput} bytes/s")
# Calculate throughput for UDP packets only
udp_throughput = df_received[df_received['pkt_type'] == 'cbr']['pkt_size'].sum() / df_received['time'].max()
print(f"UDP throughput: {udp_throughput} bytes/s")
To run this Python script, ensure you have pandas installed in your Python environment. You can install it via pip if necessary (pip install pandas). This script reads the trace file, analyzes the packets, and calculates the throughput over time for the entire link, as well as segregating the throughput by TCP and UDP packets.
This approach provides a foundational understanding of network simulation with NS-2 and basic trace analysis using Python, covering total and protocol-specific throughput computations.
vagrant iron
@harsh star $ns duplex-link $n1 $n2 1Mb 20ms DropTail # Bottleneck link how is this a bottleneck link?
harsh starBOT
<@1082069574901563453> $ns duplex-link $n1 $n2 1Mb 20ms DropTail # Bottleneck li...
The concept of a bottleneck link in network topologies, particularly in simulations like those created with NS-2, refers to a point in the network that significantly limits the overall performance due to its relatively lower capacity or higher delay compared to other links in the network. In the context of your NS-2 script snippet:
$ns duplex-link $n1 $n2 1Mb 20ms DropTail # Bottleneck link
Here's why this particular link is designated as a bottleneck:
-
Bandwidth (1Mb): The link between nodes
n1andn2is set to have a bandwidth of 1 Megabit per second (1Mb). If other links in the network have higher bandwidths, this link's lower capacity makes it the limiting factor in the amount of data that can flow through the network at any given time. For example, the link betweenn0andn1has a bandwidth of 1.5 Megabits per second (1.5Mb). The reduced bandwidth of the link betweenn1andn2means it cannot carry as much data per second as the other link, leading to potential congestion or increased queuing atn1when trying to transmit ton2. -
Delay (20ms): This link also has a delay of 20 milliseconds (20ms). The delay, or latency, represents the time it takes for data to travel from one node to another. A higher delay on a critical path can contribute to the bottleneck effect, particularly for interactive or real-time applications, by increasing the time it takes for packets to reach their destination.
-
Queue Management (DropTail): The use of
DropTailas the queue management policy means that when the queue of packets waiting to be transmitted on this link reaches its maximum size, incoming packets will be dropped until space becomes available. In scenarios where incoming packet rates exceed the link's capacity,DropTailqueues can exacerbate the bottleneck effect, as excess packets are simply dropped, potentially leading to higher retransmission rates and further reducing the effective throughput.
**In a simulation co