How to Implement Network Data Compression in NS2

To implement the Network Data Compression in NS2 is used to minimize the size of transmitted data, saving bandwidth, decreasing transmission time and optimizing the entire network performance. In NS2, replicating this can be achieved by manipulating the packet sizes at the application to indicate the impacts of compression.

While NS2 does not natively support real data compression algorithms like Huffman Coding, GZIP, or LZW, we can imitate the compression influence by decreasing the size of the data packets before transmission and restoring them at the destination.

Steps to Implement Network Data Compression in NS2

To implement data compression in NS2, you can:

  1. Reduce the packet size before transmission to simulate compression.
  2. Restore the original size at the receiving end to simulate decompression.
  3. Observe the bandwidth savings and performance improvements from the simulated compression.
  1. Set Up NS2 Environment

Make sure to install the ns2 on your computer. We will create a simulation where nodes compress data before sending and decompress data upon receiving.

  1. Create a TCL Script for Data Compression

Below is an example TCL script that demonstrates how to establish data compression in NS2. This script decreases the packet size before sending to replicate compression and logs the bandwidth savings.

Example TCL Script for Network Data Compression:

# Create a new NS2 simulator

set ns [new Simulator]

# Open trace and NAM output files

set tracefile [open data_compression.tr w]

$ns trace-all $tracefile

set namfile [open data_compression.nam w]

$ns namtrace-all $namfile

# Define wireless network parameters

set val(chan)   Channel/WirelessChannel

set val(prop)   Propagation/TwoRayGround

set val(ant)    Antenna/OmniAntenna

set val(netif)  Phy/WirelessPhy

set val(mac)    Mac/802_11

set val(ifq)    Queue/DropTail/PriQueue

set val(ifqlen) 50

set val(ll)     LL

set val(rp)     AODV                       ;# Use AODV routing protocol

set simulation_time 50.0                    ;# Duration of the simulation

# Create topography for the network

set topo [new Topography]

$topo load_flatgrid 1000 1000

# Configure node parameters

$ns node-config -adhocRouting $val(rp) \

-llType $val(ll) \

-macType $val(mac) \

-ifqType $val(ifq) \

-ifqLen $val(ifqlen) \

-antType $val(ant) \

-propType $val(prop) \

-phyType $val(netif) \

-channelType $val(chan) \

-topoInstance $topo \

-agentTrace ON \

-routerTrace ON \

-macTrace ON

# Create nodes dynamically

set num_nodes 2

for {set i 0} {$i < $num_nodes} {incr i} {

set node($i) [$ns node]

set x_pos [expr rand() * 1000]

set y_pos [expr rand() * 1000]

$node($i) set X_ $x_pos

$node($i) set Y_ $y_pos

$node($i) set Z_ 0

}

# Data compression function: Simulates data compression by reducing the packet size

proc compress_data {original_size compression_ratio} {

set compressed_size [expr $original_size * (1.0 – $compression_ratio)]

return $compressed_size

}

# Data decompression function: Restores the original data size (for simulation purposes)

proc decompress_data {compressed_size compression_ratio} {

set original_size [expr $compressed_size / (1.0 – $compression_ratio)]

return $original_size

}

# Create UDP agent for data transmission

set udp0 [new Agent/UDP]

$ns attach-agent $node(0) $udp0

# Create Null agent to receive packets at node1

set null0 [new Agent/Null]

$ns attach-agent $node(1) $null0

# Connect the UDP agent to the Null agent

$ns connect $udp0 $null0

# Create CBR traffic over the UDP agent with compression

set cbr0 [new Application/Traffic/CBR]

# Set original packet size (in bytes) and compression ratio (e.g., 50% compression)

set original_packet_size 1024

set compression_ratio 0.5

set compressed_packet_size [compress_data $original_packet_size $compression_ratio]

$cbr0 set packetSize_ $compressed_packet_size ;# Compressed packet size

$cbr0 set rate_ 1Mb

$cbr0 attach-agent $udp0

# Schedule traffic start and stop times

$ns at 1.0 “$cbr0 start”

$ns at [expr $simulation_time – 5] “$cbr0 stop”

# Log the compression details

puts “Original packet size: $original_packet_size bytes”

puts “Compressed packet size: $compressed_packet_size bytes”

puts “Compression ratio: $compression_ratio”

# Decompress the data when received at node1 (for simulation purposes)

set decompressed_size [decompress_data $compressed_packet_size $compression_ratio]

puts “Decompressed packet size (restored): $decompressed_size bytes”

# Schedule simulation end

$ns at $simulation_time “finish”

# Finish procedure to close trace and NAM files

proc finish {} {

global ns tracefile namfile

$ns flush-trace

close $tracefile

close $namfile

exec nam data_compression.nam &

exit 0

}

# Run the simulation

$ns run

  1. Explanation of Key Components
  • Compression Function: The function compress_data simulates compression by minimizing the packet size in terms of stated compression ratio. For instance, if the original packet size is 1024 bytes and the compression ratio is 50%, the compressed size will be 512 bytes.
  • Decompression Function: The function decompress_data restores the actual size of the data after transmission, simulating decompression at the receiver.
  • Traffic Generation: Use CBR (Constant Bit Rate) traffic to produce the UDP traffic from node0 to node1. The compressed packet size is used for transmission to simulate the impact of data compression.
  • Logging: The script stores the authentic, compressed, and decompressed packet sizes, granting you to monitor the influence of data compression on bandwidth utilization.
  1. Run the Simulation

Log the script as data_compression.tcl and execute it in NS2:

ns data_compression.tcl

After the simulation is done, you can visualize the network using NAM:

nam data_compression.nam

  1. Explanation of Data Compression
  • Compressed Packet Size: The packet size is decreased before transmission to mimic the impacts of compression. For instance, a 1024-byte packet is compressed to 512 bytes when a compression ratio of 50% is applied.
  • Bandwidth Savings: Minimizing the packet size outcomes in fewer bytes being transmitted through the network, saving bandwidth and capably decreasing transmission time.
  • Decompression: Upon receiving the compressed data, the decompression function restores the genuine packet size for the purpose of simulation.
  1. Advanced Features for Data Compression

You can extend this simulation by including more modern mechanisms:

  • Variable Compression Ratios: Execute various compression ratios in terms of the type of data (such as text, images, or video).
  • Real-time Compression: Imitate real-time compression by modifying packet sizes dynamically during the simulation based on network conditions (for instance: congestion).
  • Compression Algorithms: Rather than just minimizing packet size, replicate various types of compression algorithms (like lossless vs. lossy compression).
  • Energy Consumption Analysis: Assess the influence of data compression on energy usage, certainly in resource-constrained networks like Wireless Sensor Networks (WSNs).

Through this step-by-step demonstration, we make sure that you can now implement the Network Data Compression in ns2 environment and use this strategy in this simulated network to enhance the overall network performance and how to enhance it using the offered steps.

Reach out to ns2project.com for customized Network Data Compression solutions and project inspiration. Keep in communication with us for top-notch implementation advice and achieve outstanding outcomes.