How to Calculate Network DNS Management in NS2
To calculate the Network Domain Name System (DNS) Management in NS2 encompasses to simulate and observe the activities DNS that resolves domain names into IP addresses. Though NS2 mainly concentrates on packet-level simulations, it does not directly mimic DNS resolution. Yet, we can simulate DNS-based activities by generating DNS servers and clients, observing DNS query/response actions and assessing how efficiently the system resolves domain names to IP addresses.
Following guide will help you compute it in ns2:
Steps to Simulate and Calculate DNS Management in NS2
- Set Up the NS2 Simulation with DNS-Like Behavior
To replicate DNS, you can designate a node as a DNS server that resolves domain names (or simulated names) to IP addresses. Other nodes (clients) will deliver DNS queries to this server, and the server will react with the equivalent IP addresses.
Example NS2 Script for DNS Management Simulation
# Create NS2 simulator instance
set ns [new Simulator]
# Open trace file for logging DNS events
set tracefile [open dns_management_trace.tr w]
$ns trace-all $tracefile
# Define network nodes
set dns_server [$ns node] ;# Node as DNS server (simulates DNS resolution)
set client1 [$ns node] ;# Client node 1 requesting DNS resolution
set client2 [$ns node] ;# Client node 2 requesting DNS resolution
# Assign domain names and IPs manually
# DNS Server -> Resolves “www.example.com” to “192.168.1.1”
# DNS Server -> Resolves “www.example2.com” to “192.168.1.2”
# Create duplex links between nodes
$ns duplex-link $dns_server $client1 1Mb 10ms DropTail
$ns duplex-link $dns_server $client2 1Mb 10ms DropTail
# Set up UDP agents to simulate DNS query and response
set udp_server [new Agent/UDP]
$ns attach-agent $dns_server $udp_server
set udp_client1 [new Agent/UDP]
$ns attach-agent $client1 $udp_client1
$ns connect $udp_client1 $udp_server
set udp_client2 [new Agent/UDP]
$ns attach-agent $client2 $udp_client2
$ns connect $udp_client2 $udp_server
# Set up CBR traffic to simulate DNS queries from clients
set query1 [new Application/Traffic/CBR]
$query1 set packetSize_ 500
$query1 set interval_ 1.0 ;# Query interval from client1
$query1 attach-agent $udp_client1
set query2 [new Application/Traffic/CBR]
$query2 set packetSize_ 500
$query2 set interval_ 1.5 ;# Query interval from client2
$query2 attach-agent $udp_client2
# Start DNS queries from clients
$ns at 0.5 “$query1 start”
$ns at 1.0 “$query2 start”
# Stop traffic after some time
$ns at 4.0 “$query1 stop”
$ns at 4.5 “$query2 stop”
# End simulation at 5 seconds
$ns at 5.0 “finish”
proc finish {} {
global ns tracefile
$ns flush-trace
close $tracefile
exit 0
}
# Run the simulation
$ns run
Explanation:
- DNS Server: The node dns_server mimics a DNS server that resolves domain names to IP addresses.
- Clients: client1 and client2 send queries to the DNS server, ask for the resolution of domain names (e.g., “www.example.com“).
- Traffic: Constant Bit Rate (CBR) traffic simulates DNS queries and reactions, where each client delivers periodic DNS queries to the server.
- Domain Resolution: While real domain names and IP addresses are not used, the traffic simulates DNS-like activities where the server reacts to client requests.
- Simulating DNS Resolution
- Queries: In this simulation, client1 and client2 are querying the DNS server, requesting domain name resolution.
- Responses: The DNS server replies to these queries by sending back the resolved “IP address.” While NS2 does not manage original DNS responses, you can simulate the actions by tracking which queries are delivered and when responses are obtained.
- Monitor DNS Query/Response Behavior
In the trace file, you will see logs of packet transmissions indicating DNS queries from clients and reactions from the DNS server. You can use these logs to compute difference DNS management metrics like query response time, resolution success rate, and DNS server load.
- Calculate Key DNS Management Metrics
DNS Query Response Time
One of the crucial metrics in DNS management is the DNS query response time—the time it takes for the DNS server to resolve a query and respond to the client.
Here’s an AWK script to calculate DNS query response time:
awk ‘
{
if ($1 == “+” && $3 == “client1”) { # DNS query sent from client1
send_time[$7] = $2; # Record the time the query was sent
}
if ($1 == “r” && $3 == “client1”) { # DNS response received by client1
if (send_time[$7] != “”) {
response_time = $2 – send_time[$7]; # Calculate the response time
print “DNS Query Response Time for client1:”, response_time, “seconds”;
}
}
}’ dns_management_trace.tr
This script calculates the DNS query reply time by subtracting the time the query was sent from the time the response was acquired.
DNS Query Success Rate
The DNS query success rate signifies the percentage of queries that were successfully resolved by the DNS server. You can measure this by tracking how many queries were sent and how many reactions were acquired.
Here’s an AWK script to calculate DNS query success rate:
awk ‘
{
if ($1 == “+” && $3 == “client1”) { # DNS query sent from client1
total_queries_client1++;
}
if ($1 == “r” && $3 == “client1”) { # DNS response received by client1
successful_queries_client1++;
}
if ($1 == “+” && $3 == “client2”) { # DNS query sent from client2
total_queries_client2++;
}
if ($1 == “r” && $3 == “client2”) { # DNS response received by client2
successful_queries_client2++;
}
}
END {
print “DNS Success Rate for client1:”, (successful_queries_client1 / total_queries_client1) * 100, “%”;
print “DNS Success Rate for client2:”, (successful_queries_client2 / total_queries_client2) * 100, “%”;
}’ dns_management_trace.tr
This script computes the success rate by dividing the number of successful DNS responses by the total number of queries sent.
DNS Server Load
The DNS server load can be measured by tracking how many queries the server processes over time. This gives you an idea of how much traffic the DNS server is managing and whether it is being overloaded.
Here’s an AWK script to compute the DNS server load:
awk ‘
{
if ($1 == “r” && $3 == “dns_server”) { # DNS query received by DNS server
dns_queries_handled++;
}
}
END {
print “Total DNS Queries Handled by DNS Server:”, dns_queries_handled;
}’ dns_management_trace.tr
This script tracks the counts of queries processed by the DNS server during the simulation.
- Simulate DNS Cache and Performance Optimization
You can extend the simulation to attach DNS caching, where repeated DNS queries for the same domain are managed more fastly without sending a request to the authoritative server. This would involve:
- Initial query: The first query to the DNS server incurs a full response delay.
- Subsequent queries: Repeated queries for the same domain can be simulated as cached responses with decreased delays.
- Visualize DNS Metrics
Once you have calculated the DNS metrics (response time, success rate, and server load), you can visualize these results using Python (matplotlib) to get a better understanding of DNS performance.
Example Python Plot for DNS Query Response Time:
import matplotlib.pyplot as plt
# Example data for DNS response times
clients = [‘client1’, ‘client2’]
response_times = [0.03, 0.05] # Example response times in seconds
plt.bar(clients, response_times)
plt.title(‘DNS Query Response Time’)
plt.xlabel(‘Clients’)
plt.ylabel(‘Response Time (seconds)’)
plt.show()
Summary
To estimate network DNS management in NS2:
- Set up the simulation: State nodes to replicate DNS servers and clients. Use traffic to indicate DNS queries and responses.
- Monitor DNS behavior: Track DNS queries sent by clients and responses obtained from the DNS server.
- Calculate key metrics: Use AWK scripts to calculate DNS query response time, success rate, and server load.
- Simulate caching: Include caching behavior to mimic DNS performance optimization.
- Visualize results: Use tools like Python to plot DNS performance metrics like response times and success rates.
Make use of the delivered steps and instructions which will help you to focus on the computational process of Network Domain Name System (DNS) Management by setting up the simulation using ns2 tool. You can also visualize the simulation outcomes using tools like matplotlib.
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