How to Implement Data Centric Protocol in NS2

 

To implement the data-centric protocol within NS2 has needs to encompass making a protocol in which the communication is driven by the data itself instead of the network addresses or node identities. This protocol methods are general in the sensor networks that the queries are sent out to collect the data which matches particular criteria, and the nodes have the related data respond.

One familiar specimen of a data-centric protocol is Directed Diffusion. Given below is a procedure to making a simple data-centric protocol using the simulation NS2:

Step-by-Step Implementation:

Step 1: Understand Data-Centric Protocols

This protocols are concentrate on the data being transmitted instead of the particular nodes. The nodes may disseminate interests or queries regarding the data they want. The data those matches these interests is routed back to the requesting node. Common characteristics include:

  • Interest Propagation: Nodes send out interests for specific types of data.
  • Data Matching: Nodes that generate data matching an interest respond by sending the data back beside the converse path.
  • Data Aggregation: Intermediate nodes might aggregate the data to decrease redundancy.

Step 2: Set Up NS2

Make sure that NS2 is installed on the system. We can download it from the NS2 webpage and we pursue the installation instructions. Check the installation by running a simple simulation.

Step 3: Implement the Data-Centric Protocol in C++

  1. Create the Data-Centric Agent Class

We want to make a new C++ class in NS2 where executes the logic for the data-centric protocol. This agent class must handle the following:

  • Interest Propagation: These nodes are propagate interests (queries) for exact data.
  • Data Matching: Nodes with corresponding data respond to the interest.
  • Data Aggregation (Optional): Intermediate nodes are aggregate data to decrease traffic.

The following is a simple structure:

#include <agent.h>

#include <packet.h>

#include <trace.h>

#include <address.h>

#include <map>

#include <string>

class DataCentricAgent : public Agent {

public:

DataCentricAgent();

void recv(Packet* p, Handler* h);

void propagateInterest(std::string interest);

void sendData(std::string data, int dest);

void receiveData(Packet* p);

void aggregateData(std::string data);

protected:

std::map<std::string, int> interestTable_; // Interest -> Requester Node ID

std::map<int, std::string> dataTable_; // Node ID -> Data

};

// Constructor

DataCentricAgent::DataCentricAgent() : Agent(PT_UDP) {

// Initialization code here

}

// Packet reception

void DataCentricAgent::recv(Packet* p, Handler* h) {

hdr_cmn* cmnh = hdr_cmn::access(p);

hdr_ip* iph = hdr_ip::access(p);

int src = iph->src();

char* payload = (char*) p->accessdata();

if (strncmp(payload, “INTEREST”, 8) == 0) {

// Handle interest propagation

std::string interest(payload + 9); // Extract interest

propagateInterest(interest);

} else if (strncmp(payload, “DATA”, 4) == 0) {

// Handle incoming data

receiveData(p);

}

}

// Propagate interest throughout the network

void DataCentricAgent::propagateInterest(std::string interest) {

if (interestTable_.find(interest) == interestTable_.end()) {

interestTable_[interest] = addr(); // Store the interest

// Code to propagate the interest to neighbors

}

}

// Send data in response to an interest

void DataCentricAgent::sendData(std::string data, int dest) {

// Code to send data packet back to the requester

}

// Receive data that matches an interest

void DataCentricAgent::receiveData(Packet* p) {

// Code to process the received data

// Optionally, aggregate data if needed

}

// Optional: Aggregate data before forwarding

void DataCentricAgent::aggregateData(std::string data) {

// Code to aggregate data

}

  1. Integrate the Data-Centric Agent into NS2
  1. Modify the Makefile: Append the new DataCentricAgent class to the NS2 Makefile thus it acquires compiled with the rest of the simulator.
  2. Recompile NS2:

make clean

make

Step 4: Create a Tcl Script to Simulate the Data-Centric Protocol

When the data-centric protocol is executed and compiled, and make a Tcl script to mimic a network using this protocol.

Example Tcl Script:

# Create a simulator object

set ns [new Simulator]

# Define the topology

set val(chan)   Channel/WirelessChannel

set val(prop)   Propagation/TwoRayGround

set val(netif)  Phy/WirelessPhy

set val(mac)    Mac/802_11

set val(ifq)    Queue/DropTail/PriQueue

set val(ll)     LL

set val(ant)    Antenna/OmniAntenna

set val(ifqlen) 50

set val(nn)     10

set val(x)      1000

set val(y)      1000

set val(stop)   100.0

set val(rp)     DataCentric   ;# Data-Centric Protocol

# Initialize the topology object

set topo [new Topography]

$topo load_flatgrid $val(x) $val(y)

# Create the God object

create-god $val(nn)

# Configure the nodes

$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 \

-movementTrace ON

# Create nodes

for {set i 0} {$i < $val(nn)} {incr i} {

set node_($i) [$ns node]

}

# Define node positions and movement model

$node_(0) set X_ 100.0; $node_(0) set Y_ 200.0

$node_(1) set X_ 200.0; $node_(1) set Y_ 300.0

$node_(2) set X_ 300.0; $node_(2) set Y_ 400.0

$node_(3) set X_ 400.0; $node_(3) set Y_ 500.0

$node_(4) set X_ 500.0; $node_(4) set Y_ 600.0

# Propagate an interest for specific data

$ns at 5.0 “$node_(0) propagateInterest \”temperature data\””

# Simulation end

$ns at $val(stop) “stop”

$ns at $val(stop) “$ns nam-end-wireless $val(stop)”

$ns at $val(stop) “exit 0”

proc stop {} {

global ns tracefile namfile

$ns flush-trace

close $tracefile

close $namfile

}

# Run the simulation

$ns run

Step 5: Run the Simulation

  1. We can save the Tcl script like datacentric_example.tcl.
  2. Open a terminal and navigate to the directory in which we can saved the Tcl script.
  3. Run the simulation using the given command:

ns datacentric_example.tcl

Step 6: Analyse the Results

  • We can use the trace files and the network animator (NAM) to estimate the performance of the data-centric protocol that concentrate on the parameters like data delivery success, latency, and network traffic.
  • Inspect how well the protocol propagates their interests and responds with related data.

Additional Considerations

  • Data Aggregation: Execute and examine various data aggregation approaches to decrease redundancy and enhance the network performance.
  • Performance Comparison: Compare the data-centric protocol with another protocols, such as Directed Diffusion or traditional address-based routing protocols, to assess its efficiency in several scenarios.

This page had given more comprehensive informations about the procedure on how to execute and setup the Data Centric protocol in the analysis tool ns2. We will provide more valuable details concerning this topic in various tools. To Implement Data Centric Protocol in NS2 you can approach ns2project.com we will help you with novel ideas and topics.