How to Calculate Network Computational Efficiency in NS2

To calculate the Network Computational Efficiency in Network Simulator 2 (NS2), we have to evaluate how efficiently the network processes and manages data in relation to computational resources like CPU cycles or processing time. It is particularly related in situations in which nodes (for instance: routers, sensors or other devices) have restricted computational and you are interested in knowing how effectively the network usage computational resources while delivering performance.  For assistance with any type of project, please do not hesitate to reach out to us; we are committed to delivering the best results for you .In the following below, we have shown the entire steps to calculate it this in ns2:

In NS2, network computational efficiency can be indirectly analyzed by computing metrics such as:

  1. Processing Delays: The time taken by nodes to process packets.
  2. Energy Consumption due to Computation: This can be incorporated with an energy model to reflect the computational energy consumption of nodes.
  3. Throughput: The total of data successfully processed and transmitted.
  4. Packet Handling Rate: The count of packets processed per unit of time.

Steps to Calculate Network Computational Efficiency

  1. Simulation Setup:

Begin by configuring the network environment with nodes that are actively processing data (such as routing, packet forwarding or running a particular algorithm). Simulate the network load by stating traffic model (like UDP, TCP)

  1. Measure Packet Processing Time (Optional Customization):
  • In NS2, by default, there is no direct built-in mechanism to record computational load (CPU utilization, etc.), however you can estimate packet processing time or total delay to indirectly evaluate computational efficiency.
  • You can log the time a packet takes to get processed by a node (entering a node until being transferred to the next hop) by using NS2 trace files.
  1. Evaluate Throughput and Delay:
  • Throughput: The number of data successfully processed and transmitted per second.
  • Delay: The time taken for a packet to traverse the network, which contains both transmission time and processing delays.

These metrics can offer insights into how efficiently the network manages computation-heavy tasks like routing or data processing.

  1. Energy Consumption Due to Computation (Optional):
  • If you use an energy model, it’s possible to quantify the computational energy cost by allocating certain energy consumption rates for various computational tasks (processing, packet managing).
  • You can then relate the sum of data processed to the total energy used for computation.
  1. Calculate Computational Efficiency:

Network computational efficiency can be measured using the following general formula:

Computational Efficiency=Total Data Processed (bits)Computational Resources Used (e.g., CPU cycles or energy) (bits/Joule or bits/CPU cycle)\text{Computational Efficiency} = \frac{\text{Total Data Processed (bits)}}{\text{Computational Resources Used (e.g., CPU cycles or energy)}} \ (\text{bits/Joule or bits/CPU cycle})Computational Efficiency=Computational Resources Used (e.g., CPU cycles or energy)Total Data Processed (bits)​ (bits/Joule or bits/CPU cycle)

Example NS2 Tcl Script:

Here is an example NS2 script for replicating a simple network scenario where several nodes communicate using UDP. You can later extend this with custom logic to track processing delays and energy consumption.

# Create a new simulator instance

set ns [new Simulator]

# Open trace file to record events

set tracefile [open trace.tr w]

$ns trace-all $tracefile

# Define the nodes (5 nodes for this example)

set node0 [$ns node]

set node1 [$ns node]

set node2 [$ns node]

set node3 [$ns node]

set node4 [$ns node]

# Set up UDP agents for communication

set udp0 [new Agent/UDP]

set udp1 [new Agent/UDP]

set null [new Agent/Null]

# Attach agents to the nodes

$ns attach-agent $node0 $udp0

$ns attach-agent $node1 $udp1

$ns attach-agent $node4 $null

# Connect agents

$ns connect $udp0 $null

$ns connect $udp1 $null

# Create traffic sources

set cbr0 [new Application/Traffic/CBR]

$cbr0 attach-agent $udp0

$cbr0 set packetSize_ 512

$cbr0 set rate_ 1Mb

set cbr1 [new Application/Traffic/CBR]

$cbr1 attach-agent $udp1

$cbr1 set packetSize_ 512

$cbr1 set rate_ 1Mb

# Schedule traffic

$ns at 1.0 “$cbr0 start”

$ns at 2.0 “$cbr1 start”

$ns at 4.0 “$cbr0 stop”

$ns at 5.0 “$cbr1 stop”

# Define finish procedure

proc finish {} {

global ns tracefile

$ns flush-trace

close $tracefile

exit 0

}

# Schedule the end of simulation

$ns at 6.0 “finish”

$ns run

  1. Trace File Analysis for Computational Efficiency:

The trace file will contain details about when packets are sent (s), received (r), or dropped (d). You can assess these events to measure the computational performance of the network. Here’s how you can do that:

  1. Packet Handling Time:
    • Quantify the time difference amongst a packet being delivered from a node and being obtained at another node to infer the total time taken for processing.
    • The trace file is used to analyze these events.
  2. Throughput:
    • Compute how many packets (in bits) were successfully received during the simulation time.

Example Bash script to calculate throughput:

# Count the total packets received by node4

received_packets=$(grep “^r” trace.tr | grep “_4_” | wc -l)

# Define packet size in bits (512 bytes = 4096 bits)

packet_size=4096

# Calculate total data received (bits)

total_data_received=$(echo “$received_packets * $packet_size” | bc)

# Simulation time in seconds (example: 5 seconds)

simulation_time=5

# Throughput calculation (bits per second)

throughput=$(echo “scale=2; $total_data_received / $simulation_time” | bc)

echo “Throughput: $throughput bits/second”

  1. Energy/Processing Time Analysis:
    • You can combine node-specific processing delays or power consumption models to calculate the computational resources used. This can be achieved by either logging node idle, transmission, and reception times or by using custom event handling logic.
  1. Computational Efficiency Formula:

Assuming you measure total data processed (in bits) and computational resources used (based on processing time, CPU cycles, or energy):

Computational Efficiency (bits/CPU cycle or bits/Joule)=Total Data Processed (bits)Total Processing Resources (CPU cycles or energy)\text{Computational Efficiency (bits/CPU cycle or bits/Joule)} = \frac{\text{Total Data Processed (bits)}}{\text{Total Processing Resources (CPU cycles or energy)}}Computational Efficiency (bits/CPU cycle or bits/Joule)=Total Processing Resources (CPU cycles or energy)Total Data Processed (bits)​

If you choose to concentrate on energy consumption:

# Calculate computational efficiency (bits per Joule)

if [ $energy_consumed -gt 0 ]; then

computational_efficiency=$(echo “scale=2; $total_data_received / $energy_consumed” | bc)

echo “Computational Efficiency: $computational_efficiency bits/Joule”

else

echo “No energy consumed.”

fi

In this step-by-step approach, we had clearly explored the detailed process on how to set up the simulation environment to measure the computational efficiency in the ns2 by Packet Processing Time and analysing the throughput and delay. If you need any additional information, let us know so that we will guide you.