Network Traffic Simulator

In the field of networking, various topics and plans for projects are emerging recently that include modern technology and robust simulators. We suggest a list of few project topics which can be investigated through network traffic simulators potentially:

  1. Simulation of DDoS Attack and Mitigation Techniques
  • Goal: On simulated network threats, research the efficacy of various Distributed Denial of Service (DDoS) reduction methods.
  • Procedure: To evaluate the efficiency in maintaining network accessibility, apply different reduction policies like rate limiting and traffic filtering and create a network under threat by simulating DDoS traffic.
  1. Performance Analysis of SD-WAN under Varying Traffic Conditions
  • Goal: In handling and improving network traffic under various criteria, observe the efficiency of Software-Defined Wide Area Network (SD-WAN) technology.
  • Procedure: Keep more trustworthiness and efficiency using application-attentive routing and traffic steering by simulating an SD_WAN setting with multiple traffic figures and network criteria to check its capacity.
  1. Evaluating the Impact of IPv6 Adoption on Network Traffic
  • Goal: Aiming at routing performance, packet overhead and tackling and then, exploring the influence of changing from IPv4 to IPv6 on network traffic activity.
  • Procedure: To observe the variations in routing ability and traffic efficiency, employ network simulation to design networks which work on IPv4, IPv6 and double-stack configurations.
  1. QoS Evaluation in Multimedia Networks
  • Goal: Target on parameters like packet loss, latency and jitter and evaluate the quality of service (QoS) in the network transferring multimedia aspect.
  • Procedure: By utilizing different QoS systems to assess their efficiency in confirming a high-standard user experience, simulate a network transmitting practical audio and video streams.
  1. Traffic Load Balancing in Data Center Networks
  • Goal: To enhance application efficacy and resource implementation, create and assess methods for dynamic traffic load equaling in data center networks.
  • Procedure: In terms of latency, throughput and network congestion, observe the frameworks influence, apply different load equaling approaches and develop a data center network with the help of a network simulator.
  1. Wireless Network Congestion and Control Strategies
  • Goal: During more traffic volumes, it is necessary to minimize latency and maximize throughput by discovering congestion control policies in wireless networks.
  • Procedure: Detect the most efficient ideas under different situations by designing a congested wireless network platform and validating various congestion control approaches.
  1. Network Traffic Anomaly Detection Using Machine Learning
  • Goal: To identify abnormalities in network traffic which can point-out network breakdowns or safety attacks, create machine learning frameworks.
  • Procedure: Check their effectiveness and precision in abnormality identification, simulate network traffic with and without abnormalities and then implement the data to instruct machine learning frameworks.
  1. Impact of Routing Protocols on IoT Network Performance
  • Goal: Based on the data supply, scalability, energy consumption, it observes how the efficacy of IoT networks is impacted by various routing protocols.
  • Procedure: Specifically in restricted network platforms, simulate an IoT network with the assistance of different routing protocols like AODV or RPL and observe their effect on efficiency.
  1. The Effect of Mobility on Ad-hoc Network Performance
  • Goal: By aiming at the performance of routing protocols and network connections, observe the influence of node mobility on the strength of mobile ad-hoc networks (MANETs).
  • Procedure: Discover plans to preserve network connections, research the efficacy of various routing protocols and simulate a MANET with different node mobility degrees.
  1. Traffic Engineering in MPLS Networks
  • Goal: To enhance network application and optimize the running of traffic, assess traffic engineering methods in Multiprotocol Label Switching (MPLS) networks.
  • Procedure: On bandwidth implementation and traffic dispersion, design an MPLS network, apply traffic engineering ideas and evaluate their influence by using network simulation.

How do I establish communication between nodes in NS2 and pass messages saying that there is traffic ahead?

       Particularly, you have to develop a network topology, configure the nodes to employ a unique interaction protocol such as UDP or TCP, and then develop and transfer packets which transport your message to set up interaction among nodes in Network Simulator 2 (NS-2) and forward messages like an alerting about traffic earlier. By aiming at an ad-hoc network setting which is usual for broadcasting traffic details, we will summarize a simple method to achieve this task. The following example is mostly implemented for disseminating messages such as traffic notifications and it will utilize UDP for message forwarding especially for its simplicity:  

Step 1: Define the Topology

       To explain your network topology and configurations, you have to develop a Tcl script initially. Begin by establishing an ad-hoc network platform and describing the nodes:

# Create a simulator object

set ns [new Simulator]

# Define a topology object

set topo [new Topography]

# Define the area of the network

$topo load_flatgrid 500 500

# Create a God object (used for ad-hoc networking simulations)

create-god 2

# Open the Nam trace file

set tracefile [open out.nam w]

$ns namtrace-all-wireless $tracefile 500 500

# Define a procedure to finish the simulation

proc finish {} {

    global ns tracefile

    $ns flush-trace

    close $tracefile

    exec nam out.nam &

    exit 0


# Create two nodes

set n0 [$ns node]

set n1 [$ns node]

# Position the nodes

$n0 set X_ 250

$n0 set Y_ 250

$n0 set Z_ 0.0

$n1 set X_ 300

$n1 set Y_ 250

$n1 set Z_ 0.0

Step 2: Establish Communication Protocol

       You can create UDP links among the nodes in this step. You should prepare n0 and transfer a message to n1 for ease.

# Create a UDP agent for n0

set udp0 [new Agent/UDP]

$ns attach-agent $n0 $udp0

# Create a null agent (a sink) for n1 to receive the message

set null0 [new Agent/Null]

$ns attach-agent $n1 $null0

# Connect the UDP and null agents

$ns connect $udp0 $null0

# Set up a UDP source to generate traffic

set cbr0 [new Application/Traffic/CBR]

$cbr0 set packetSize_ 500

$cbr0 set interval_ 0.5

$cbr0 attach-agent $udp0

Step 3: State the Message

       For your particular message such as traffic ahead, you must modify the packet data. As NS-3 highly works with transmission rates, intervals and packet sizes, it does not assist routine text messages straight to packets in a simple manner. But you can consider that a packet being sent denotes your “traffic ahead” message for simulation motives.

       You may require to employ a temporary solution like mentioning packet sizes and breaks or expand the C++ program of NS-2’s to denote various kinds of messages, when you have to simulate the concept of the messages entirely.

Step 4: Begin the Simulation

# Schedule events

$ns at 1.0 “$cbr0 start”

$ns at 5.0 “$cbr0 stop”

# Call finish after simulation ends

$ns at 6.0 “finish”

# Run the simulation

$ns run

Step 5: Running the Simulation

       The .tcl extension is used to save your script, For instance, traffic_sim.tcl. Apply the given command in your terminal to execute your simulation:

ns traffic_sim.tcl

Network Traffic Simulator Projects

Network Traffic Simulator Project Topics & Ideas

Network Traffic Simulator Project offers a glimpse into the exciting world of projects that can be accomplished using network simulators. Our team has successfully completed numerous simulator projects and received rave reviews from customers all around the globe. Simulation is a thriving field where we excel in delivering top-notch results. At, our esteemed researchers are dedicated to guiding scholars towards excellence. With a plethora of network simulators and various networking domains, we are here to provide you with countless innovative ideas tailored to your specific concept.

  1. Short-Term Strategies for Class of Service Differentiation in IP over Optics Network
  2. Joint Optimization in Software Defined Wireless Networks with Network Coded Opportunistic Routing
  3. Research and implementation of distributed intelligent network fault management system
  4. Scalability analysis of machine learning QoT estimators for a cloud-native SDN controller on a WDM over SDM network
  5. Demonstration of SDN Based Optical Network Virtualization and Multidomain Service Orchestration
  6. A Literature Review of Resiliency Technologies in Military Software Defined Networks
  7. Optimisation Methods for Dynamic Frequency Planning in OFDMA Networks
  8. Reliable and Low-Overhead Clustering in LEO Small Satellite Networks
  9. Research on management architecture for Home NodeB access network
  10. Web-based configurable connection management objects over open information networking
  11. SDN based load balancing mechanism for elephant flow in data center networks
  12. Darkstar: Using exploratory data mining to raise the bar on network reliability and performance
  13. A Shapley value-based forwarding strategy in Information-Centric Networking
  14. A solution to network protocol issues for directional ad-hoc networks through topology control and a multiple-radio-per-node architecture
  15. Logical optical line terminal placement optimization in the elastic lambda aggregation network with optical distribution network constraints
  16. Inter-Session Network Coding with Clustering Routing in Wireless Delay Tolerant Networks
  17. Evolution of all-optical networks; IP centric photonic network development
  18. Evolving existing narrowband networks towards broadband networks with IN capabilities
  19. Impact of Network Density on the Performance of Delay Tolerant Protocols in Heterogeneous Vehicular Network
  20. Provisioning radio access networks for effective QoS management: capacity gains of service differentiation in UTRAN


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