How to Implement Network Performance Analysis in NS2
To implement the Network Performance Analysis in NS2 encompasses to analyze the vital metrics of the performance includes throughput, delay, packet loss, jitter and bandwidth consumption that help to analyze how well the network performs in different conditions like numerous traffic loads, network topologies or routing protocols.
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Here’s a step-by-step guide on how to implement Network Performance Analysis in NS2:
Step-by-Step Guide to Implement Network Performance Analysis in NS2
- Set Up the Basic Network Topology:
- First, configure the simplified network topology that contains nodes and links. This network will serve as the environment for performance analysis.
Example OTcl script for setting up a simple wired topology:
set ns [new Simulator]
set nf [open out.tr w]
$ns trace-all $nf
set namfile [open out.nam w]
$ns namtrace-all $namfile
# Create nodes
set node0 [$ns node] ;# Source node
set node1 [$ns node] ;# Intermediate node
set node2 [$ns node] ;# Destination node
# Create duplex links between nodes
$ns duplex-link $node0 $node1 1Mb 10ms DropTail
$ns duplex-link $node1 $node2 1Mb 10ms DropTail
# Define TCP communication between node0 and node2
set tcp [new Agent/TCP]
set sink [new Agent/TCPSink]
$ns attach-agent $node0 $tcp
$ns attach-agent $node2 $sink
$ns connect $tcp $sink
set ftp [new Application/FTP]
$ftp attach-agent $tcp
# Start the FTP traffic at 1.0 seconds and stop at 5.0 seconds
$ns at 1.0 “$ftp start”
$ns at 5.0 “$ftp stop”
# Run the simulation
$ns at 6.0 “finish”
proc finish {} {
global ns nf namfile
$ns flush-trace
close $nf
close $namfile
exec nam out.nam &
exit 0
}
$ns run
- This script designs a basic three-node network where TCP traffic flows from node0 to node2 via node1.
- Monitor Performance Metrics:
Perform network performance analysis by observing and recording key metrics like throughput, delay, packet loss, and jitter.
2.1 Throughput:
- Throughput computes the rate of successful packet delivery through a network link. To compute throughput, you can assess the count of bytes acquired by the destination node over a period of time.
Example AWK script to calculate throughput:
awk ‘{
if ($1 == “r” && $4 == “TCP”) {
total_bytes += $6
}
} END {
print “Throughput: “, total_bytes / 5, “bytes per second”
}’ out.tr
- This script estimates the total number of bytes received by the destination node (node2) over the 5 seconds of the simulation and computes the throughput.
2.2 Packet Delay (End-to-End Delay):
- End-to-End Delay measures the time taken for a packet to move from the source to the destination.
Example AWK script to calculate packet delay:
awk ‘{
if ($1 == “s” && $4 == “TCP”) {
start_time[$11] = $2
}
if ($1 == “r” && $4 == “TCP”) {
end_time[$11] = $2
total_delay += end_time[$11] – start_time[$11]
packet_count++
}
} END {
print “Average Delay: “, total_delay / packet_count, “seconds”
}’ out.tr
- This script tracks the delivering and receiving times of TCP packets and calculates the average end-to-end delay for the entire transmission.
2.3 Packet Loss:
- Packet Loss happens when packets fail to reach their destination. Packet loss can be a result of network blockage, faulty links, or dropped packets because of buffer overflows.
Example AWK script to calculate packet loss:
awk ‘{
if ($1 == “s” && $4 == “TCP”) {
sent_packets++
}
if ($1 == “r” && $4 == “TCP”) {
received_packets++
}
} END {
packet_loss = sent_packets – received_packets
print “Total Packet Loss: “, packet_loss
}’ out.tr
- This script sums the amount of packets sent by the source and received by the destination to define how many were lost during transmission.
2.4 Jitter:
- Jitter measures the variation in packet delay and is vital for applications like voice and video communication.
Example AWK script to calculate jitter:
awk ‘{
if ($1 == “r” && $4 == “TCP”) {
if (prev_time != 0) {
delay_diff = $2 – prev_time
jitter += (delay_diff > 0) ? delay_diff : -delay_diff
}
prev_time = $2
packet_count++
}
} END {
print “Average Jitter: “, jitter / packet_count, “seconds”
}’ out.tr
- This script estimates the average jitter by summing up the variation in delay amongst successive packets.
2.5 Bandwidth Utilization:
- Bandwidth Utilization denotes the percentage of existed network capacity used during the transmission.
Example calculation for bandwidth utilization:
awk ‘{
if ($1 == “r” && $4 == “TCP”) {
total_bytes += $6
}
} END {
utilization = (total_bytes * 8) / (5 * 1e6) * 100 # 1Mb link over 5 seconds
print “Bandwidth Utilization: “, utilization, “%”
}’ out.tr
- This script measures the percentage of bandwidth consumed by TCP traffic on the 1Mb link.
- Analyze Traffic Patterns:
- In addition to observing performance metrics, you can replicate different traffic patterns to assess how the network performs under various conditions.
Example OTcl script to simulate several traffic flows:
# Define a second TCP connection amongst node1 and node2
set tcp2 [new Agent/TCP]
set sink2 [new Agent/TCPSink]
$ns attach-agent $node1 $tcp2
$ns attach-agent $node2 $sink2
$ns connect $tcp2 $sink2
set ftp2 [new Application/FTP]
$ftp2 attach-agent $tcp2
# Start second traffic flow at 2.0 seconds
$ns at 2.0 “$ftp2 start”
- This script configures another TCP flow from node1 to node2, permitting you to monitor the network’s performance with several concurrent traffic flows.
- Run the Simulation and Collect Data:
- Execute the simulation to gather trace data on network performance.
To run the simulation:
ns your_script.tcl
- The trace file (out.tr) will log detailed information about packet transmissions, delays, losses, and other network events.
- Analyze Performance Metrics Using AWK Scripts:
- Use the AWK scripts offered in step 2 to evaluate key performance metrics like throughput, delay, packet loss, and jitter.
Example AWK command to calculate throughput:
awk -f throughput.awk out.tr
- Similarly, run the other AWK scripts for delay, packet loss, and jitter analysis.
- Visualize Network Performance in NAM:
- NAM (Network Animator) is used to visualize network performance in real-time. You can monitor traffic flows, packet drops, and link consumption.
To include NAM:
nam out.nam
- In NAM, you can visually examine how the network acts under various conditions, assissting you correlate visual patterns with the computed performance metrics.
In this simulation technique, we derived some instructions on how to compute the metrics of the performance analysis of the network and how to deploy them using ns2 simulator. If you have any concerns or need any details, we will offer it through another report.