How to Calculate Network Policy Enforcement in NS2

To calculate Network policy enforcement in ns2 has includes to implement and tracking the certain rules that rule on how traffic flows in a network. These guidelines can control access, restrict specific types of traffic, prioritize specific data flows, or implement security measures such as firewalls. In NS2, we can mimic policy enforcement by implement custom rules that filter, prioritize, or restrict traffic, and then evaluate on how the network responds to these policies.

To calculate network policy enforcement in NS2, you need to:

  1. Describe network policies, like traffic filtering, access control, or Quality of Service (QoS).
  2. Execute these policies using NS2’s capabilities, like traffic filtering and link control.
  3. Evaluate the impact of these policies by estimating parameters such as packet drops, throughput, latency, and packet prioritization.

Steps to Simulate and Calculate Network Policy Enforcement in NS2

  1. Set up the Network Simulation

We will mimic a simple network with a central node acting as a policy enforcer. This node will implements policies such as:

  • Traffic filtering: Blocking or permitting traffic based on certain rules.
  • QoS enforcement: Selecting traffic based on type such as prioritizing TCP over UDP.

Example NS2 Script with Policy Enforcement

# 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

set n0 [$ns node]   ;# Client node

set n1 [$ns node]   ;# Policy enforcement node

set n2 [$ns node]   ;# Server node

# Create duplex links between nodes

$ns duplex-link $n0 $n1 1Mb 10ms DropTail

$ns duplex-link $n1 $n2 1Mb 10ms DropTail

# Set up UDP traffic from n0 to n2 (through policy node n1)

set udp0 [new Agent/UDP]

$ns attach-agent $n0 $udp0

set null0 [new Agent/Null]

$ns attach-agent $n2 $null0

$ns connect $udp0 $null0

set cbr0 [new Application/Traffic/CBR]

$cbr0 set packetSize_ 500

$cbr0 set interval_ 0.01

$cbr0 attach-agent $udp0

# Set up TCP traffic from n0 to n2 (through policy node n1)

set tcp0 [new Agent/TCP]

$ns attach-agent $n0 $tcp0

set sink0 [new Agent/TCPSink]

$ns attach-agent $n2 $sink0

$ns connect $tcp0 $sink0

set ftp0 [new Application/FTP]

$ftp0 attach-agent $tcp0

# Start and stop traffic

$ns at 0.5 “$cbr0 start”

$ns at 0.5 “$ftp0 start”

$ns at 4.5 “$cbr0 stop”

$ns at 4.5 “$ftp0 stop”

# Define a policy: prioritize TCP over UDP

proc policy_enforce {src dst type} {

if {$type == “UDP”} {

return 0  ;# Drop all UDP traffic to prioritize TCP

}

return 1  ;# Allow TCP traffic

}

# Apply policy enforcement at 0.5 seconds

$ns at 0.5 “$ns set-forwarding-filter policy_enforce”

# 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:

  • Policy Enforcement Node: Node n1 behaves as the central node that implements network policies. It filters and selects traffic.
  • Traffic: Both UDP and TCP traffic flow from node n0 (client) to node n2 (server) across the policy node n1.
  • Policy: The script blocks all UDP traffic to contribute higher priority to TCP traffic. This policy is applied using the policy_enforce function, that filters traffic in term of its type.
  1. Implement Policy Enforcement

We can execute numerous network policies by adjusting how packets are forwarded, dropped, or prioritized. The script above enforces a simple traffic prioritization policy; however we can expand the rules to contain:

  • Bandwidth allocation: Limit bandwidth for certain types of traffic.
  • Access control: permit or deny traffic according to source or destination IP/port.
  • QoS enforcement: select a certain kinds of traffic or make sure low-latency for critical flows.
  1. Capture Data from the Trace File

NS2 creates a trace file (out.tr) that logs key events like packet enqueue (+), dequeue (-), and drop (d). By measuring this trace file, we can evaluate the impacts of the policy enforcement on the network.

Parameters to capture include:

  • Packet drops: Monitor how many packets were dropped due to policy enforcement.
  • Throughput: Measure how much traffic was successfully forwarded.
  • Latency: Evaluate the delay in packet transmission among nodes.
  1. Calculate Policy Enforcement Metrics

Packet Drops Due to Policy

We can sum up on how many packets were dropped because of the enforcement of network policies such as blocking UDP traffic.

Here’s an AWK script to estimate the number of packet drops triggered by the policy:

awk ‘

{

if ($1 == “d” && $3 == “n1”) {  # Count drops at the policy node

dropped_packets++;

}

}

END { print “Total Packets Dropped by Policy:”, dropped_packets; }’ out.tr

This script summing up on how many packets were dropped at node n1 because of policy enforcement (e.g., dropping UDP traffic).

Throughput of Allowed Traffic

Throughput defined to the amount of traffic that was successfully forwarded by the policy enforcement node.

Here’s an AWK script to estimate the throughput of allowable traffic (e.g., TCP):

awk ‘

{

if ($1 == “-” && $3 == “n1” && $4 == “n2” && $6 == “TCP”) {

total_bytes += $6;  # Count total TCP bytes forwarded by the policy node

}

}

END { print “TCP Throughput:”, total_bytes / 5.0, “bytes/sec”; }’ out.tr

This script estimate the throughput by count the total number of bytes forwarded by node n1 to node n2 for TCP traffic.

Latency of Forwarded Traffic

We can estimate the latency of the allowed traffic like TCP by evaluating the time it takes for a packet to travel from node n0 to node n2 through the policy enforcement node.

Here’s an AWK script to estimate average latency:

awk ‘

{

if ($1 == “+”) {

send_time[$7] = $2;  # Record the time a packet is sent from n0

}

if ($1 == “-” && $3 == “n1” && $4 == “n2” && $6 == “TCP”) {

if (send_time[$7] != “”) {

latency = $2 – send_time[$7];  # Calculate latency for TCP traffic

total_latency += latency;

count++;

}

}

}

END { print “Average Latency for TCP Traffic:”, total_latency / count, “seconds”; }’ out.tr

This script estimates the average latency for TCP traffic as it passes via the policy enforcement node.

  1. Enhance the Policy Enforcement

We can extend the policy enforcement by adding more complex rules, like:

  • Port-based filtering: permit or block traffic in terms source/destination port.
  • IP-based filtering: Control traffic based on IP addresses.
  • Rate limiting: Limit the bandwidth available for specific traffic types such as limit UDP traffic to 100 kbps.

Example: Rate Limiting UDP Traffic

proc policy_enforce {src dst type} {

if {$type == “UDP”} {

set max_rate 100000  ;# Limit UDP to 100 kbps

if {[expr $ns get-link-traffic-rate $src $dst] > $max_rate} {

return 0  ;# Drop packets exceeding the rate limit

}

}

return 1  ;# Allow other traffic

}

  1. Visualize Policy Enforcement Performance

We can envision parameters like packet drops, throughput, and latency using tools such as Python (matplotlib) or Excel. For instance, we can plot the throughput of TCP and UDP traffic over time to demonstration the impact the policy enforcement.

Example Python Plot for TCP Throughput:

import matplotlib.pyplot as plt

# Example data for TCP throughput over time

time = [0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0, 4.5]

throughput = [600, 650, 700, 750, 800, 850, 900, 950, 1000]  # Example throughput data (bytes/sec)

plt.plot(time, throughput, marker=’o’)

plt.title(‘TCP Throughput Over Time’)

plt.xlabel(‘Time (seconds)’)

plt.ylabel(‘Throughput (bytes/sec)’)

plt.grid(True)

plt.show()

Summary

To mimic and estimate network policy enforcement in NS2:

  1. Set up the simulation: Generate a network with a central node that implements policies.
  2. Implement policies: Describe rules to regulate traffic, like filtering or selecting the certain kinds of traffic.
  3. Capture trace data: Measure the trace file to evaluate the effect of policy enforcement on packet drops, throughput, and latency.
  4. Enhance policies: Execute more advanced policies such as rate limiting or IP-based filtering.
  5. Visualize results: Use envision tools to measure the impact of policy enforcement on network performance.

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