How to Calculate Network Proxies in NS2
To calculate the network proxy in ns2 has needs to generate a middle node that interrupts and forwards traffic among clients and servers. A proxy node usually behave as an intermediary that whichever caches, filters, or forwards requests on behalf of a client. Since NS2 does not have built-in support for proxy-specific characteristics, we can mimic proxy behaviour by setting up a node to forward traffic among nodes and estimating proxy-related metrics like latency, throughput, and packet filtering.
Here is a brief approach on how to achieve this approach:
Steps to Simulate and Calculate Network Proxies in NS2
- Set up a Proxy Node
A proxy node will sit among the source (client) and destination (server) nodes. This proxy node wills accelerative traffic among the client and server, mimic proxy performance. We can also describe certain rules for the proxy, like caching or filtering traffic.
Here’s an instance NS2 script to mimic a basic proxy:
Example NS2 Script to Simulate a Proxy Node
# Create NS2 simulator instance
set ns [new Simulator]
# Open trace file for output
set tracefile [open out.tr w]
$ns trace-all $tracefile
# Define nodes (proxy is n1)
set client [$ns node] ;# Client node
set proxy [$ns node] ;# Proxy node
set server [$ns node] ;# Server node
# Create duplex links between client and proxy, and proxy and server
$ns duplex-link $client $proxy 1Mb 10ms DropTail
$ns duplex-link $proxy $server 1Mb 10ms DropTail
# Set up UDP traffic from client to server (through proxy)
set udp0 [new Agent/UDP]
$ns attach-agent $client $udp0
set null0 [new Agent/Null]
$ns attach-agent $server $null0
$ns connect $udp0 $null0
set cbr0 [new Application/Traffic/CBR]
$cbr0 set packetSize_ 500
$cbr0 set interval_ 0.005
$cbr0 attach-agent $udp0
# Start and stop traffic
$ns at 0.5 “$cbr0 start”
$ns at 4.5 “$cbr0 stop”
# End simulation
$ns at 5.0 “finish”
proc finish {} {
global ns tracefile
$ns flush-trace
close $tracefile
exit 0
}
# Run the simulation
$ns run
Explanation of the Script:
- Proxy Node: The node proxy behaves as the intermediary (proxy) among the client (client) and the server (server).
- Links: The proxy node is associated to both the client and the server through duplex links.
- Traffic: The client sends traffic to the server; nevertheless the traffic is transmitted via the proxy node.
- Monitor Proxy Behaviour
NS2 will create a trace file (out.tr) that logs events such as packet enqueueing, dequeueing, transmission, and drops. By measuring this trace file, we can estimate key proxy parameters like latency, throughput, and filtering.
- Calculate Proxy Metrics
Proxy Latency
Latency is the delay established by the proxy. It can be estimated by evaluating the time it takes for a packet to travel from the client to the server via the proxy. This has involves the time spent at the proxy.
Here’s an AWK script to estimate the average proxy latency:
awk ‘
{
if ($1 == “+”) {
send_time[$7] = $2; # Record the time a packet is sent from the client
}
if ($1 == “-” && $3 == “proxy” && $4 == “server”) {
if (send_time[$7] != “”) {
latency = $2 – send_time[$7]; # Calculate latency through the proxy
total_latency += latency;
count++;
}
}
}
END { print “Average Proxy Latency:”, total_latency / count, “seconds”; }’ out.tr
This script analyses the time it takes for packets to travel from the client to the server via the proxy and calculates the average latency.
Throughput through the Proxy
Throughput is the total number of packets successfully forwarded by the proxy. We can estimate throughput by summing up the number of bytes forwarded by the proxy to the server.
Here’s an AWK script to calculate throughput:
awk ‘
{
if ($1 == “-” && $3 == “proxy” && $4 == “server”) { # Forwarded by proxy to server
total_bytes += $6; # Sum the total bytes forwarded by the proxy
}
}
END { print “Proxy Throughput:”, total_bytes / 5.0, “bytes/sec”; }’ out.tr
This script estimates the throughput by count the total number of bytes forwarded by the proxy and dividing it by the simulation time (5 seconds).
Packet Drops at the Proxy
We can mimic filtering behaviour at the proxy by dropping packets in terms of particular rules like blocking certain kinds of traffic or limiting traffic by source/destination. We can sum up on how many packets are dropped at the proxy because of filtering or buffer overflow.
Here’s an AWK script to count packet drops at the proxy:
awk ‘
{
if ($1 == “d” && $3 == “proxy”) { # Count packets dropped by the proxy
dropped_packets++;
}
}
END { print “Total Packets Dropped at Proxy:”, dropped_packets; }’ out.tr
This script counts on how many packets were dropped by the proxy node, that can denote packet filtering or buffer overflows.
- Add Proxy Filtering or Caching Rules
We can extend the proxy’s functionality by executing traffic filtering or caching rules. For sample, we can generate a custom procedure to filter traffic based on packet size, source address, or type of traffic (UDP/TCP).
Example: Blocking UDP Traffic at the Proxy
proc proxy_filter {src dst type} {
if {$type == “UDP”} {
return 0 ;# Block all UDP traffic
}
return 1 ;# Allow all other traffic
}
# Apply proxy filtering rule to block UDP traffic
$ns at 0.5 “$ns set-forwarding-filter proxy_filter”
In this instance, the proxy blocks all UDP traffic. We can extend this rule to filter according to an IP addresses, ports, or other parameters.
- Analyze Proxy Performance
By measuring the parameters, we can measure the proxy’s impact on network performance, which has:
- Increased latency due to traffic passing via an intermediary.
- Throughput reduction if the proxy is overloaded or dropping packets.
- Packet filtering or drops if the proxy is configured to block particular traffic types.
- Visualize Proxy Metrics
We can envision key proxy parameters like latency and throughput using tools such as Python (matplotlib) or Excel. Here’s an sample of how to plot the proxy throughput over time:
Example Python Plot for Proxy Throughput:
import matplotlib.pyplot as plt
# Example data for proxy throughput over time
time = [0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0, 4.5]
throughput = [500, 600, 650, 700, 750, 800, 850, 900, 950] # Example throughput data (bytes/sec)
plt.plot(time, throughput, marker=’o’)
plt.title(‘Proxy Throughput Over Time’)
plt.xlabel(‘Time (seconds)’)
plt.ylabel(‘Throughput (bytes/sec)’)
plt.grid(True)
plt.show()
Summary
To mimic and compute network proxy behavior in NS2:
- Set up a proxy node: Generate a central node that forwards traffic among the client and the server.
- Simulate proxy behavior: Capture traffic passing via the proxy and implement optional filtering or caching rules.
- Capture metrics: Use the trace file to compute proxy parameters like latency, throughput, and packet drops.
- Expand functionality: Add filtering or caching rules to replicate more complex proxy behaviours.
- Visualize metrics: Use tools such as Python or Excel to plot and measure the proxy’s effects on network performance.
We demonstrate and provide the valuable insights on how to calculate and simulate the results for network proxy in ns2 tool. If you need more details regarding the network proxy we will provide it.
Reach out to ns2prject.com for details about your Network Proxies in the NS2 tool, and we will support you with creative project ideas and topics. Obtain assistance in evaluating proxy-related metrics such as latency, throughput, and packet filtering for your initiatives.