Network Simulator

IEEE NS3 Projects List

  • September 30 2023
  • Bhimsen

NS3 Simulator project

IEEE 2023 NS3 project list for mtech / MS / be / btech / mca / M.sc students in bangalore

1.A Distributed Prevention Scheme from Malicious Nodes in VANETs’ Routing Protocols

Vehicular situations are helpless against assaults due to the consistent collaborations between vehicles in spite of verification methods sent by correspondence guidelines. Actually, a verified hub with a testament could start an assault while following actualized conventions in the event that it has malevolent goals and advantage from this dependably on association to undermine the system precision. A few instruments to counter these assaults were proposed yet none of them can foresee the conduct of hubs.

In the present work, we focus on this issue by proposing a preventive component ready to anticipate the conduct of vehicles and keep from assaults. We utilize Kalman channel to anticipate the future conduct of vehicles and order them into three classes (white, dim and dark) in light of their normal dependability. The primary worry of this work is to anticipate from the disavowal of administration (DoS) assault. Results, given bydistributed-prevention-scheme-from-malicious-nodes

Project Overview :

The proposed system is in view of a grouped engineering where a bunch head (CH) is accountable for the checking and grouping of vehicles in the fitting records (White, Gray and Black). The CH continuously screens its individuals, ascertains their trust-levels based on its involvement with them and got suggestions from different hubs that are painstakingly picked and actuated to be observing specialists.

System Requirement
Hardware Requirement
System : Pentium IV 2.4 GHz.
Hard Disk : 40 GB.
Monitor : 15 inch VGA Color.
Mouse : Logi tech Mouse.
Ram : 512 MB
Keyboard : Standard Keyboard
Software Requirement
Operating System : LINUX
Tool : Network Simulator-3
Front End : C++
Scripting : Python,awk

Sample Code
NS_LOGNS_LOG_COMPONENT_DEFINE (“WifiSimpleOcb”);
void ReceivePacket (Ptr socket)
{
while (socket->Recv ())
{
NS_LOG_UNCOND (“Received one packet!”);
}
}
static void GenerateTraffic (Ptr socket, uint32_t pktSize,
uint32_t pktCount, Time pktInterval )
{
if (pktCount > 0)
{
socket->Send (Create (pktSize));
Simulator::Schedule (pktInterval, &GenerateTraffic,
socket, pktSize,pktCount – 1, pktInterval);
}
else
{
socket->Close ();
}
}NS_LOG_COMPONENT_DEFINE (“WifiSimpleOcb”);
void ReceivePacket (Ptr socket)
{
while (socket->Recv ())
{
NS_LOG_UNCOND (“Received one packet!”);
}
}
static void GenerateTraffic (Ptr socket, uint32_t pktSize,
uint32_t pktCount, Time pktInterval )
{
if (pktCount > 0)
{
socket->Send (Create (pktSize));
Simulator::Schedule (pktInterval, &GenerateTraffic,
socket, pktSize,pktCount – 1, pktInterval);
}
else
{
socket->Close ();
}
}NS_LOG_COMPONENT_DEFINE (“WifiSimpleOcb”);
void ReceivePacket (Ptr socket)
{
while (socket->Recv ())
{
NS_LOG_UNCOND (“Received one packet!”);
}
}

Code Explanation
This code helps to generate the vanet traffic between two nodes,applcations are created by the function. void ReceivePacket (Ptr socket) to demonstrate the receive packet

 

2.Analytical Model and Performance Evaluation of Long Term Evolution for Vehicle Safety Services

In traffic jam or dense vehicle environment, vehicular ad-hoc networks (VANET) can’t meet safety requirement due to serious packet collision. The traditional cellular network solves packet collision, but suffers from long end-to-end delay. 3GPP Long Term Evolution (LTE) overcomes both drawbacks, thus it may be used instead of VANET in some extreme environments. We use Markov models with the dynamic scheduling and semi-persistent scheduling (SPS) to evaluate how many idle resources of LTE can be provided for safety services and how safety applications impact on LTE traditional users. Based on the analysis, we propose to reserve the idle radio resources in LTE for vehicular safety services (LTE-V). Additionally, we propose the weighted-fair-queueing (WFQ) algorithm to schedule beacons for safety services using LTE reserved resource. Numerical results verify that the proposed mechanism can significantly improve the reliability of safety application by borrowing limited LTE bandwidth.

analytical-model-vehicle-safety-services

System Requirements

Hardware Requirement
System : Pentium IV 2.4 GHz.
Hard Disk : 40 GB.
Monitor : 15 inch VGA Color.
Mouse : Logi tech Mouse.
Ram : 512 MB
Keyboard : Standard Keyboard
Software Requirement
Operating System : LINUX
Tool : Network Simulator-3
Front End : C++
Scripting : Python,awk


Sample Code
Sample Code
using namespace ns3;
int main (int argc, char *argv[])
{
CommandLine cmd;
cmd.Parse (argc, argv);
ConfigStore inputConfig;
inputConfig.ConfigureDefaults ();
cmd.Parse (argc, argv);
Ptr lteHelper = CreateObject ();
lteHelper->SetAttribute ("PathlossModel", StringValue ("ns3::FriisSpectrumPropagationLossModel"));
NodeContainer enbNodes;
NodeContainer ueNodes;
enbNodes.Create (1);
ueNodes.Create (3);
MobilityHelper mobility;
mobility.SetMobilityModel ("ns3::ConstantPositionMobilityModel");
mobility.Install (enbNodes);
mobility.SetMobilityModel ("ns3::ConstantPositionMobilityModel");
mobility.Install (ueNodes);
NetDeviceContainer enbDevs;
NetDeviceContainer ueDevs;
enbDevs = lteHelper->InstallEnbDevice (enbNodes);
ueDevs = lteHelper->InstallUeDevice (ueNodes);
lteHelper->Attach (ueDevs, enbDevs.Get (0));
enum EpsBearer::Qci q = EpsBearer::GBR_CONV_VOICE;
EpsBearer bearer (q);
lteHelper->ActivateDataRadioBearer (ueDevs, bearer);
Simulator::Stop (Seconds (0.5));
lteHelper->EnablePhyTraces ();
lteHelper->EnableMacTraces ();
lteHelper->EnableRlcTraces ();
double distance_temp [] = { 1000,1000,1000};
std::vector userDistance;
userDistance.assign (distance_temp, distance_temp + 3);
for (int i = 0; i < 3; i++)
{
Ptr mm = ueNodes.Get (i)->GetObject ();
mm->SetPosition (Vector (userDistance[i], 0.0, 0.0));
}
Simulator::Run ();
Simulator::Destroy ();
return 0;
}
Code Explaination Enb nodes and uenodes,are created uedevs .It have enabled the distance between the nodes and also called userDistance.assign(distance_temp, distance_temp + 3);Mobility has been set using Ptr mm = ueNodes.Get (i)->GetObject ();

 

3.Performance of The Routing Protocols AODV, DSDV and OLSR in Health Monitoring Using NS3

The complexity of health care and the increasing cost of health care in developing country such as Indonesia caused by the source of available funds and limited human resources, especially health professionals. Health monitoring through wireless body area network is one of the solution and which offers several advantages as inexpensive health services, better utilization from health care professional resource, mobility, and great experience for the patient.

However, health monitoring has some challenges such as limited area coverage, mobility problem and attenuation from human body. In this paper, it describes how to research about utilization AODV, DSDV, and OLSR routing protocols from ad hoc network to improve health monitoring by using NS3 to face limited area coverage and mobility problem for static and mobile conditions. As simulation, the researcher compares the performance of AODV, DSDV, and OLSR.


The researcher selected three performances of metrics: delay, throughput, and packet delivery ratio. As a result showed, OLSR has better performance for mobile and mobile has more than 50 nodes except delay, when throughput, and packet delivery ratio of mobile condition OLSR show better than AODV . In static condition, throughput of AODV shows better than DSDV and OLSR, even though for mobile condition OLSR shows better than AODV and DSDV, but in some cases the delay of AODV shows better than DSDV and OLSR. This is an indication for the possible implementation of OLSR routing protocols which node is bigger than 50 nodes.

routing-protocols

Project Overview
Impromptu system offers a few favorable circumstances helping well being checking to run significantly as self-governing framework. By utilizing independent framework, each hub can be associated itself with different hubs for alternate patients to change or send a data to screen the server.

Each hub in the system can serve transmitting own information or wiped out a hand-off for another hub in the system to transmit other patient information to adjacent expert medicinal services utilizing a assortment of directing convention which is accessible. Another focal points are self mending and self setup, it is extremely supportive to help our hub for portable conditions.

System Configuration

Hardware Requirement
System : Pentium IV 2.4 GHz.
Hard Disk : 40 GB.
Monitor : 15 inch VGA Color.
Mouse : Logi tech Mouse.
Ram : 512 MB
Keyboard : Standard Keyboard
Software Requirement
Operating System : LINUX
Tool : Network Simulator-3
Front End : C++
Scripting : Python,awk

Sample Code
NS_LOG_COMPONENT_DEFINE ("manet-routing-compare");
class RoutingExperiment
{
public:RoutingExperiment ();
void Run (int nSinks, double txp, std::string CSVfileName);//static void SetMACParam
(ns3::NetDeviceContainer & devices,
// int slotDistance);
std::string CommandSetup (int argc, char **argv);
private:
Ptr SetupPacketReceive (Ipv4Address addr, Ptr node);
void ReceivePacket (Ptr socket);
void CheckThroughput ();
uint32_t port;
uint32_t bytesTotal;
uint32_t packetsReceived;
std::string m_CSVfileName;
int m_nSinks;
std::string m_protocolName;
double m_txp;
bool m_traceMobility;
uint32_t m_protocol;
};
Code Explanation
This code explains how we are experimenting the routing and QOS performance calculation such as throughput,totoal packets received,total bytes sent. This should be performed for all the protocol and should be compared.

 

4.Fast and Smooth Data Delivery Using MPTCP by Avoiding Redundant Retransmissions

We introduce a new, simple, yet effective scheme for reducing the impact of receiver buffer blocking in Multipath TCP (MPTCP). This blocking primarily occurs when the paths have different characteristics. his phenomenon is due to the limited size of the MPTCP receiver buffer. In a nutshell, our scheme allows, under certain conditions, the retransmission of a segment by a different interface than the one used originally and the closure of the badly behaving TCP connection.

Our scheme anticipates the problem by opening multiple TCP connections for each interface, but only uses one at a given time. It detects when a segment needs to be retransmitted from another interface,closes the ongoing connection on the original interface, and starts using one of the backup connections.

data-delivery-using-mptcp

Project Overview
There are two critical segments of the proposed plot. The first is the scheduler that relegates the portions to the subflows. The second is the location of an issue taken after by the choice regardless of whether to switch interfaces for a retransmission and close the dynamic TCP association. We utilize the most reduced Round Trip Time (RTT) first scheduler and we propose calculations to identify if interface resetting is required.

System Configuration
Hardware Requirement
System : Pentium IV 2.4 GHz.
Hard Disk : 40 GB.
Monitor : 15 inch VGA Color.
Mouse : Logi tech Mouse.
Ram : 512 MB
Keyboard : Standard Keyboard

Software Requirement
Operating System : LINUX
Tool : Network Simulator-3
Front End : C++
Scripting : Python,awk
Sample Code
namespace ns3 {
+
+NS_OBJECT_ENSURE_REGISTERED (AttributeProbe);
+
+TypeId
+AttributeProbe::GetTypeId ()
+{
+ static TypeId tid = TypeId ("ns3::AttributeProbe")
+ .SetParent ()
+ .AddConstructor ()
+ ;
+ return tid;
+}
Code Explanation
This is a sample code explaining the registration of attribute and to get the attribute type id using he function +AttributeProbe::GetTypeId

 

5.Design of transmission manager in heterogeneous WSNs

The present age of sensor systems are intended to be application-particular, hence are presented just to a constrained set of clients. The developing idea of IoT is relied upon to house numerous applications with assorted defer prerequisites. A transmission director gives an ideal transmission time to transmitting the cushioned estimations. In the writing, arrangements have been proposed improving mostly for single detecting foundations.

In this work, we initially propose an ideal transmission administrator that backings numerous applications in a solitary jump remote sensor systems. At that point, we expand our arrangement into a dispersed transmission director to work in multi-bounce WSNs. Both transmission supervisors work couple, also, decide the transmission time for each supported estimation.

We execute the two arrangements in ns3 and think about with other best in class arrangements. Our contextual analyses demonstrate that our proposed arrangement diminishes vitality utilization by 75% contrasted with the best in class approaches while having all things considered 12% less lapsed estimations.

transmission-manager-in-heterogeneous

Project Overview :
In this work, we initially propose an ideal transmission supervisor utilizing the ideal ceasing hypothesis in light of Markov Decision Process demonstrate (MDP) keeping in mind the end goal to get the ideal transmission occurrence between a couple of hubs. At that point, we propose an appropriated transmission director that changes the ideal transmission administrator to work in multi-jump WSNs. The ideal and circulated transmission directors work couple, and keep running on every hub.
System Specifications

Hardware Requirement
System : Pentium IV 2.4 GHz.
Hard Disk : 40 GB.
Monitor : 15 inch VGA Color.
Mouse : Logi tech Mouse.
Ram : 512 MB
Keyboard : Standard Keyboard
Software Requirement
Operating System : LINUX
Tool : Network Simulator-3
Front End : C++
Scripting : Python,awk

Sample Code
// ping6.SetRemote (Ipv6Address::GetAllNodesMulticast ());
ping6.SetAttribute ("MaxPackets", UintegerValue (maxPacketCount));
ping6.SetAttribute ("Interval", TimeValue (interPacketInterval));
ping6.SetAttribute ("PacketSize", UintegerValue (packetSize));
ApplicationContainer apps = ping6.Install (nodes.Get (0));
apps.Start (Seconds (2.0));
apps.Stop (Seconds (10.0));
AsciiTraceHelper ascii;
lrWpanHelper.EnableAsciiAll (ascii.CreateFileStream ("ping6wsn.tr"));
lrWpanHelper.EnablePcapAll (std::string ("ping6wsn"), true);
NS_LOG_INFO ("Run Simulation.");
Simulator::Run ();
Simulator::Destroy ();
NS_LOG_INFO ("Done.");
}

 

6.Process Parameter Estimation Oriented Industrial Wireless Sensor Networks: A Sequential Approach

Process parameter estimation, to a large extent, determines the quality of the industrial production. Traditionally, limited sensors are deployed in production field by elaborate wiring, which cannot provide the accurate estimate in the hostile industrial environment. Recently, industrial wireless sensor network (IWSN) has been considered as one promising technology to improve the process parameter estimation by deploying more sensors flexibly and making them work collaboratively.

In this paper, a sequential IWSN (Seq-IWSN) approach is provided for the temperature estimation of the steel slab during the hot strip milling process. In Seq-IWSN, the network deployment and scheduling strategies coupling with the process parameter estimation algorithm are involved.

processparameter

Project Overview
In this paper, we exploit IWSN to enhance the temperature estimation of the steel section for harsh processing process. Related outcomes can likewise be received for other genius cess stages or other modern process parameter estimation situations. To evaluate the temperature of the steel piece some time recently it enters the harsh plant faces a few difficulties. In the first place, the steel chunk moves along the exchanging table.

Subsequently, the arrangement what's more, coordination of IWSN should adjust to the development to guarantee that the section can be inspected and the system can be fittingly worked. Second, the temperature condition of the steel section is time-changing. To secure the exact estimation before unpleasant processing, the IWSN ought to be fit to persistently track the temperature of the piece when it moves along the table.


System Configuration
Hardware Requirement
System : Pentium IV 2.4 GHz.
Hard Disk : 40 GB.
Monitor : 15 inch VGA Color.
Mouse : Logi tech Mouse.
Ram : 512 MB
Keyboard : Standard Keyboard
Software Requirement
Operating System : LINUX
Tool : Network Simulator-3
Front End : C++
Scripting : Python,awk

Sample Code
NS_LOG_INFO ("Create channels.");
LrWpanHelper lrWpanHelper;// Add and install the LrWpanNetDevice for each node
// lrWpanHelper.EnableLogComponents();
NetDeviceContainer devContainer = lrWpanHelper.Install(nodes);
lrWpanHelper.AssociateToPan (devContainer, 10);
std::cout << "Created " << devContainer.GetN() << " devices" << std::endl;
std::cout << "There are " << nodes.GetN() << " nodes" << std::endl;
/* Install IPv4/IPv6 stack */
NS_LOG_INFO ("Install Internet stack.");
InternetStackHelper internetv6;
internetv6.SetIpv4StackInstall (false);
internetv6.Install (nodes);
Code Explanation
This code explains how we are creating channels and getting attached with devices.Internet stack creation also done with the assignment of ipv4 addresses.

 

7.Mobility Quantification for MultiPoint Relays Selection Algorithm in Mobile Ad Hoc Networks

In Mobile Ad hoc Networks (MANETs), with Enhanced Link State Routing Protocol (OLSR) the versatility idea is a basic component which can bring about the advancement of system exhibitions. In this paper, the principle objective is to build up a calculation to enhance the MultiPoint Relay (MPR) determination process in such systems. This calculation depends on the Mobility Rate (MR) which thus is depended on the relative speed of hubs.

Furthermore, in this calculation, every hub keeps a portability rate record of different hubs.
In addition, this portability esteem will be traded between hubs utilizing OLSR messages (HELLO and Topology control (TC)). Moreover, this esteem will be utilized as a measure when a hub picks their MPR set. Moreover, the recreation comes about utilizing Network Test system 3 (NS3) have demonstrated that the versatility idea could enhance arrange exhibitions as far as the throughput, parcel got, bundle misfortune, bundle conveyance proportion and bundle sent. Also, and through this paper the proposed calculation can be utilized as an utilitarian portability component to enhance arrange exhibitions in MANETs.

mobility-quantification-for-multipoint-relays.png

Project Overview
The first proposed a proficient system cartography accumulation plot that is in view of OLSR flagging movement. The second one planned an improved adaptation of OLSR in light of the gathered cartography what's more, adapted properly to the effect of hubs portability. The third one proposed an arrangement of reenactments to analyze unique OLSR with CE-OLSR.

System Configuration
Hardware Requirement
System : Pentium IV 2.4 GHz.
Hard Disk : 40 GB.
Monitor : 15 inch VGA Color.
Mouse : Logi tech Mouse.
Ram : 512 MB
Keyboard : Standard Keyboard
Software Requirement
Operating System : LINUX
Tool : Network Simulator-3
Front End : C++
Scripting : Python,awk

Sample Code void (Ptr socket) {OLSR ManetExample::ReceivePacket
NS_LOG_UNCOND (Simulator::Now ().GetSeconds () << " Received one packet!");
Ptr packet;
while ((packet = socket->Recv ())
{
bytesTotal += packet->GetSize ();
packetsReceived += 1;
}
}
Code Explanation
This sample code explain the how olsr protocol helps to take the packets out and it helps the selects the multipoint relay node.and also it explains the packet received by the node with the help of function olsr Manet Example: Receive Packet.

 

8.Performance Analysis of Multicast Routing Protocols Using NS-3

Mobility of users and enhancement of bandwidth have been characterizing factors for the global telecommunication development which also witnessed improvements in services. If user needs to send some information over the prescribed bandwidth with dure reliability then the (QOS) Quality of services becomes more critical and seeks expected performance. A Mobile Adhoc Network is self-possessed combination of mobile nodes. It has to be self-structured.


These are mobility extensions into wireless domain and autonomous mobile dominion. In this set of specified nodes which form adhoc network with routing infrastructure too. Multicasting is responsible for transferring information efficiently from a source to any destination; duplication of messages and delivery takes place only once and that too at the branch points, due to splitting of the destination links.

The authors have successfully been able to address several issues relating to MANET, especially multicasting, its routing protocols and qualitative comparisons. Further, in this paper, we particularly focused on implementation as well as performance analysis of multicast routing protocols like AODV, MAODV using network simulator NS3.By using the performance parameter such as average end-to-end delay and packet delivery ratio (PDR) and routing-overhead.performance-analysis-of-multicast-routing-protocols

Project Overview :

Due to a solid multicast, a procedure can multicast a solitary message to a gathering of procedures interestingly that guarantees that all gathering individuals in the host goal amass can get the same message regardless of whether a portion of the individuals are suspiciously flawed. Multiparty cryptographic conventions and secure circulated administrations are frequently fabricated utilizing multicasts.
System Configuration

Hardware Requirement
System : Pentium IV 2.4 GHz.
Hard Disk : 40 GB.
Monitor : 15 inch VGA Color.
Mouse : Logi tech Mouse.
Ram : 512 MB
Keyboard : Standard Keyboard
Software Requirement
Operating System : LINUX
Tool : Network Simulator-3
Front End : C++
Scripting : Python,awk

Sample Code
int main(int argc,char * argv[])
{
Config::SetDefault (“ns3::CsmaNetDevice::EncapsulationMode”, StringValue (“Dix”));
CommandLine cmd;
cmd.Parse (argc, argv);
NS_LOG_INFO (“Create nodes.”);
NodeContainer c;
c.Create (5);
NodeContainer c0 = NodeContainer (c.Get (0), c.Get (1), c.Get (2));
NodeContainer c1 = NodeContainer (c.Get (2), c.Get (3), c.Get (4));
NS_LOG_INFO (“Build Topology.”);
CsmaHelper csma;
csma.SetChannelAttribute (“DataRate”, DataRateValue (DataRate (5000000)));
csma.SetChannelAttribute (“Delay”, TimeValue (MilliSeconds (2)));
NetDeviceContainer nd0 = csma.Install (c0); // First LAN
NetDeviceContainer nd1 = csma.Install (c1); // Second LAN
NS_LOG_INFO (“Add IP Stack.”);
InternetStackHelper internet;
internet.Install (c);
NS_LOG_INFO (“Assign IP Addresses.”);
Ipv4AddressHelper ipv4Addr;
ipv4Addr.SetBase (“10.1.1.0”, “255.255.255.0”);
ipv4Addr.Assign (nd0);
ipv4Addr.SetBase (“10.1.2.0”, “255.255.255.0”);
ipv4Addr.Assign (nd1);
NS_LOG_INFO (“Configure multicasting.”);
Ipv4Address multicastSource (“10.1.1.1”);
Ipv4Address multicastGroup (“225.1.2.4”);
Ipv4StaticRoutingHelper multicast;
Ptr multicastRouter = c.Get (2); // The node in question
Ptr inputIf = nd0.Get (2); // The input NetDevice
NetDeviceContainer outputDevices; // A container of output NetDevices
outputDevices.Add (nd1.Get (0)); // (we only need one NetDevice here)
multicast.AddMulticastRoute (multicastRouter, multicastSource,
multicastGroup, inputIf, outputDevices);
Code Explanation
This code explains how we are implementing the multicast routing by the creation of 5 nodes with the help of c.Create (5); ip address is assigned with the object ipv4Addr; Ipv4AddressHelper ipv4Addr; Multicast routing performance by t he commands: Ipv4Address multicast Source (“10.1.1.1”); Ipv4Address multicast Group (“225.1.2.4”); Ipv4StaticRoutingHelper multicast;

 

9.Wireless Facility Scheduling for Data Center Networks

The control parcels in the Data Center Networks (DCNs) need to challenge with the information parcels despite the fact that they are generally substantially shorter in size and significantly more vital in arrange administration. Besides, the uneven appropriation of the parcels may make potential hotspots in the DCN which could corrupt system execution radically.

To connect these holes, a couple of proposition have been advanced to develop additional remote offices in the DCNs to help advance the execution of the control activity and ease the weight of the hotspots. In any case, little consideration has been paid on the most proficient method to proficiently plan the remote offices. In this paper, a booking technique is advanced which contains two stages, i.e. course estimation and stream booking. In the previous advance, a course set between every hub match is ascertained ahead of time for later use. At that point, arrived information and control streams are booked as per numerous arrangements in view of the given course sets in the stream planning step.

wireless-facility

Project Overview :
In this paper, a scheduling method is put forward which contains two steps, i.e. route calculation and flow scheduling. In the former step, a route set between each node pair is calculated in advance for later usage. Then, arrived data and control flows are scheduled according to multiple policies based on the given route sets in the flow scheduling step.
System Configuration
Hardware Requirement
System : Pentium IV 2.4 GHz.
Hard Disk : 40 GB.
Monitor : 15 inch VGA Color.
Mouse : Logi tech Mouse.
Ram : 512 MB
Keyboard : Standard Keyboard
Software Requirement
Operating System : LINUX
Tool : Network Simulator-3
Front End : C++
Scripting : Python,awk
Sample Code
NS_LOG_COMPONENT_DEFINE ("DataCenter1");
int main (int argc, char *argv[])
{
bool verbose = true;

if (verbose)
{
LogComponentEnable ("UdpEchoClientApplication", LOG_LEVEL_INFO);
LogComponentEnable ("UdpEchoServerApplication", LOG_LEVEL_INFO);
}
//Add 1 core switch
//Construct the upper Network coragg11,coragg12,coragg21,coragg22. coragg11:core1->agg1
//ptpNodes
NodeContainer coragg11,coragg12,coragg21,coragg22;
coragg11.Create(2);
coragg12.Add(coragg11.Get(0));
coragg12.Create(1);
coragg21.Create(1);
coragg21.Add(coragg11.Get(1));
coragg22.Add(coragg21.Get(0));
coragg22.Add(coragg12.Get(1));
Code Explanation Here we have added the UDP Echo client and server application, to enable the wireless facility, Four wireless nodes have been created, and attached to the network to DCN to communicate.

 

10.Mobility Quantification for MultiPoint Relays Selection Algorithm in Mobile Ad Hoc Networks

In Mobile Ad hoc Networks (MANETs), with Optimized Link State Routing Protocol (OLSR) the mobility concept is an essential element which can result in the evolution of network performances. In this paper, the main objective is to develop an algorithm to improve the MultiPoint Relay (MPR) selection process in such networks.

This algorithm is based on the Mobility Rate (MR) which in turn is relied on the relative velocity of nodes. Additionally, in this algorithm, each node keeps a mobility rate record of other nodes. Moreover, this mobility value will be exchanged between nodes using OLSR

messages (HELLO and Topology control (TC)). Furthermore, this value will be used as a criterion when a node chooses their MPR set. In addition, the simulation results using Network Simulator 3 (NS3) have shown that the mobility concept could improve network performances in terms of the throughput,

packet received, packet loss, packet delivery ratio and packet forwarded. Moreover, and through this paper the proposed algorithm can be used as a functional mobility mechanism to improve network performances in MANETs.

 

11.Determining the network throughput and flow rate using GSR and AAL2R

In multi-radio wireless mesh networks, one node is eligible to transmit packets over multiple channels to different destination nodes simultaneously. This feature of multi-radio wireless mesh network makes high throughput for the network and increase the chance for multi path routing. This is because the multiple channel availability for transmission decreases the probability of the most elegant problem called as interference problem which is either of interflow and intraflow type.

For avoiding the problem like interference and maintaining the constant network performance or increasing the performance the WMN need to consider the packet aggregation and packet forwarding. Packet aggregation is process of collecting several packets ready for transmission and sending them to the intended recipient through the channel, while the packet forwarding holds the hop-by-hop routing.

But choosing the correct path among different available multiple paths is most the important factor in the both case for a routing algorithm. Hence the most challenging factor is to determine a forwarding strategy which will provide the schedule for each node for transmission within the channel. In this research work we have tried to implement two forwarding strategies for the multi path multi radio WMN as the approximate solution for the above said problem.

We have implemented Global State Routing (GSR) which will consider the packet forwarding concept and Aggregation Aware Layer 2 Routing (AAL2R) which considers the both concept i.e. both packet forwarding and packet aggregation. After the successful implementation the network performance has been measured by means of simulation study

 

12.A Comparative Performance Analysis of Routing Protocols in MANET using NS3 Simulator

Due to frequent topology changes and routing overhead, selection of routing protocol in Mobile Ad-hoc Network (MANET) is a great challenge. A design issue for an efficient and effective routing protocol is to achieve optimum values of performance parameters under network scenarios. There are various routing protocols available for MANET.

This paper involves study of four routing protocols (Ad-hoc On Demand Distance Vector Routing, Optimized Link State Routing, Dynamic Source Routing and Distance Sequenced Distance Vector), and performance comparisons between these routing protocols on the basis of performance metrics (throughput, packet delivery ratio, Packet dropped, jitter and end to end delay measured after simulation of network) with the help of NS3 Simulator.

 

13.Architecture and Implementation of An Information-Centric Device-to-Device Network

Today’s mobile devices almost exclusively connect to infrastructures for communications and information access; but advances such as AirDrop andWiFi Direct are bringing device to-device communication to the forefront of mobile computing. Self-organizing ad hoc mobile networks have a wide range of applications in scenarios where infrastructure is not available or with limited bandwidth, such as communications in the aftermath of natural disasters, censorship resistant communications, and battlefield communications. In this paper, we propose an information-centric device-to-device network, called ICD2D.

The network is distributed and requires no centralized coordination. For each published item of data, the system creates a metatdata; a publish-subscribe mechanism disseminates the metadata and facilitates filtering information in a distributed fashion. We implemented a full-featured system on NS3. Evaluations show significant improvement in successful information retrieval compared with OLSR (Optimized Link State Routing), a common approach to ad hoc routing.

 

14.Increasing network lifetime by energy-efficient routing scheme for OLSR protocol

One of the main considerations in designing routing protocols for Mobile Ad-Hoc Network (MANET) is to increase network lifetime by minimizing nodes’ energy consumption, since nodes are typically battery powered. Many proposals have been addressed to this problem; however, few papers consider a proactive protocol like Optimized Link State Routing Protocol (OLSR) to better manage the energy  consumption.

Some of them have explored modifications to the MPRs selection mechanism, whereas others have investigated multiple cross layer parameters to increase the network lifetime. In this paper, we explored both modification to MPR selection and integrating appropriate routing metrics in the routing decision scheme to lessen effects of reason that lead to more energy consumption. Our power-aware version of OLSR is proven by simulations in NS3 under a range of different mobile scenarios. Significant performance gains of 20% are obtained in network lifetime for our modified OLSR and little to no performance gains in term of Packet Delivery Ratio (PDR).

 

15.An NS3 Implementation of physical layer based on 802.11 for utility maximization of WSN

A Technology require to meet customer demands and improve the performance in WLAN 802.11.Wireless is a scalable, reliable and cost effective technology which can be used to implement 802.11 for utility maximization of WSN. Integrate physical layer simulator for OFDM-based IEEE 802.11 communication in a network simulator. We implement OFDM-based IEEE 802.11 standard, more precisely, for the orthogonal frequency division multiplexing (OFDM) PHY specification for the 5 GHz band.

PhySim-Wifi is a detailed and accurate implementation of the OFDM-based IEEE 802.11 standard, with higher fidelity at the physical layer than found in NS3. It can be used as replacement for the official YansWifiPhy implementation when higher simulation accuracy is required in NS3. Which will provide channel related access information in dynamic network scenario. This can lead to a programmable interface for management and control of physical layer and network layer resources in an optimal fashion.

 

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