Computer Network Simulator

Computer network simulators like NS-2/NS-3, OMNeT++, Mininet, etc are worked by us, if you want best guidance for Computer network simulators online, we are ready to provide you with. Get step wise project help with novel topics from ns3-code.com. In computer network simulations, the graph outcomes could be acquired and visualized by following several important guidelines. To acquire and visualize graph outcomes from these simulations, we suggest a common procedure. For diverse network simulators such as Mininet, OMNeT++, NS-2/NS-3, and others, this procedure can be relevant:

Step 1: Simulation Arrangement and Data Gathering

  1. Model the Network: Our network topology has to be arranged. It could encompass traffic generators (example: for TCP, UDP flows), connections (with delay and bandwidth features), and nodes (such as clients, servers, switches, and routers).
  2. Execute the Simulation: For the specified timeline, the simulation process must be carried out. To gather important data metrics (for instance: packet drop rate, delay over time, and throughput per second), we should confirm that our simulator is arranged in an appropriate manner.
  3. Record Data: Our simulation platform must record the significant data, and assuring this aspect is crucial. The simulator should return data metrics to files. According to this requirement, set up the simulator. To facilitate in-depth analysis afterwards, the data has to be recorded, including adequate level of detail (for instance: recording throughput for each second).

Step 2: Data Processing

  1. Retrieve Important Data: Consider the unprocessed data files once completing the simulation. To retrieve significant metrics, we have to process these files. To analyze log files and retrieve the required details, scripts must be utilized (for instance: Perl, Python).
  2. Aggregate Data: Plan to combine or average data points (As an instance: Consider averaging throughput for each 10 seconds) based on the amount of data and the level of detail.

Step 3: Graphical Visualization

  1. Select a Visualization Tool: Specifically for the purpose of data visualization, several tools are accessible. It could involve Excel, R, Python (including libraries such as Seaborn, Pandas, and Matplotlib), and MATLAB. On the basis of the required graph intricacy and our expertise, we should select the appropriate tool.
  2. Arrange Data for Plotting: For the visualization tool, our data must be arranged in a proper manner. Various processes such as developing matrices (for MATLAB) or data frames (for Python/Pandas) could be encompassed.
  3. Create Graphs: In order to generate graphs, the visualization tool should be utilized. To plot throughput across time, a simple instance is offered by us with Python’s Matplotlib:

import matplotlib.pyplot as plt

import pandas as pd

# Example: Loading data from a CSV file

data = pd.read_csv(‘throughput_data.csv’)

time = data[‘Time’]

throughput = data[‘Throughput’]

plt.figure(figsize=(10, 6))

plt.plot(time, throughput, label=’Throughput over Time’)

plt.xlabel(‘Time (seconds)’)

plt.ylabel(‘Throughput (Mbps)’)

plt.title(‘Network Throughput Simulation Results’)

plt.legend()

plt.grid(True)

plt.show()

  1. Examine and Interpret: To understand the functionality of our network, we need to examine the graphs after having them. Any evolving patterns, barriers, points, and tendencies have to be explored.

Step 4: Documenting Outcomes

  1. Document the Discoveries: In our simulation document, the graphs should be encompassed. Our study based on the functionality of the network has to be described. Regarding the depiction of graphs, provide explicit details.
  2. Discuss Impacts: Functionality enhancement and impacts for network models must be explained in terms of our discoveries. Consider how the examined metrics could be impacted by variations to the network.

What are some good mini project topics for a third year undergraduate in computer networking

Computer networking is a fast emerging domain that offers a wide range of opportunities to carry out research and develop projects. Related to this domain, we list out a few intriguing projects that can familiarize you with the latest mechanisms and assist to improve your knowledge of networking principles. For future exploration or advancement, these projects could even stimulate effective plans.

  1. Network Performance Analysis using Wireshark
  • Goal: To seize and examine network traffic, employ Wireshark that is considered as a network protocol analyzer. Across different conditions, the functionality of various protocols (for instance: UDP vs. TCP) could be compared in this study.
  • Acquired Expertise: Network troubleshooting, protocol behavior, and packet analysis.
  1. Simple SDN Controller Implementation
  • Goal: By means of the current SDN environment such as OpenDaylight or Ryu, we plan to create a simple Software-Defined Networking (SDN) controller. In terms of network congestion, basic missions such as dynamic flow routing could be handled by the controller.
  • Acquired Expertise: Network programmability, Python programming, and SDN infrastructure.
  1. IoT Network Security Analysis
  • Goal: In an IoT (Internet of Things) network system, the safety issues have to be explored. A compact IoT platform could be configured in this project. Along with reduction policies, general security hazards (for instance: a man-in-the-middle assault) should be depicted.
  • Acquired Expertise: Cybersecurity techniques, network security, and IoT protocols.
  1. Building a VPN Service
  • Goal: Through the utilization of open-source tools such as OpenVPN, a Virtual Private Network (VPN) service has to be configured. In this project, a VPN server must be arranged. Client links have to be initialized. Then, examine the encrypted traffic to test the configuration.
  • Acquired Expertise: Authentication protocols, encryption, and network security.
  1. Wireless Network Optimization
  • Goal: Carry out experimentations with various platforms and settings to enhance the functionality of a wireless network. Across diverse contexts, evaluate signal resilience, throughput, and interference by utilizing efficient tools.
  • Acquired Expertise: Troubleshooting, network enhancement methods, and wireless networking concepts.
  1. Simulation of Routing Protocols
  • Goal: Various routing protocols (such as RIP, BGP, and OSPF) have to be simulated with the aid of a network simulator such as OMNeT++ or NS-3. In a controlled platform, we intend to compare the functionality of these protocols.
  • Acquired Expertise: Performance analysis, network simulation, and routing algorithms.
  1. DNS Server Setup and Security
  • Goal: A Domain Name System (DNS) server has to be configured. Then, the DNS security extensions (DNSSEC) should be investigated. In this project, focus on arranging a caching DNS server. It is significant to utilize DNSSEC. Contrary to DNS spoofing assaults, exhibit the security.
  • Acquired Expertise: Network security techniques, server arrangement, and DNS infrastructure.
  1. Network Automation with Ansible
  • Goal: By employing an IT automation tool such as Ansible, general missions have to be automated, such as network arrangement and handling. To arrange network devices, collect network condition data, or implement variations, the process of writing Ansible playbooks could be encompassed.
  • Acquired Expertise: Configuration handling, YAML syntax, and network automation.
  1. IPv6 Deployment Plan
  • Goal: For shifting the current IPv4 network to IPv6, we aim to develop an extensive strategy. An IPv6 address system has to be modeled. Then, dual-stack network devices have to be arranged. It is crucial to assure connectivity and compatibility.
  • Acquired Expertise: Dual-stack platforms, network planning, and IPv6 arrangement and characteristics.
  1. Cloud Networking with AWS or Azure
  • Goal: To build and arrange a cloud-related network, make use of cloud services such as Azure or AWS. In this project, a Virtual Private Cloud (VPC) has to be created. Focus on arranging firewalls and routers related to the cloud. Then, cloud-based networking services should be investigated.
  • Acquired Expertise: Network safety in the cloud, cloud service provider tools, and cloud networking principles.

For assisting you to acquire and visualize graph outcomes from computer network simulations, a common procedure is offered by us clearly. Relevant to the computer networking field, we recommended several interesting projects, along with explicit goals and acquired expertise.

Computer Network Simulator Projects

Computer Network Simulator Projects  with source code for all programming languages are carried out by us, if you are struck in any of your work then feel free to contact us, we provide you with best solution.

  1. Time-dependent Vehicle Routing Problem with Departure Time and Speed Optimization for Shared Autonomous Electric Vehicle Service
  2. A new approach to narrow waterways traffic routing with potential flow theory and CFD
  3. Hybrid deep learning model based on Intelligent Microbat Routing (IMR) and Popularity Content Caching (PCC) for an effective caching and routing in vehicular edge networks
  4. A simulation-based metro train scheduling optimization incorporating multimodal coordination and flexible routing plans
  5. A column generation-based heuristic for a rehabilitation patient scheduling and routing problem
  6. Cross-regional manpower scheduling and routing problem with stochastic service times in home health care
  7. A memetic algorithm for a relocation-routing problem in green production of gas considering uncertainties
  8. Research on Cold Chain Routing Optimization of Multi-distribution Center Considering Traffic Performance Index
  9. Modified power line system-based energy efficient routing protocol to improve network life time in 5G networks
  10. Developing a region-based energy-efficient IoT agriculture network using region- based clustering and shortest path routing for making sustainable agriculture environment
  11. E-ARCP: An exact solution approach to the Collaborative Multi-vehicle Prize Collecting Arc Routing for Connectivity Problem
  12. Bibliometric analysis and system review of vehicle routing optimization for emergency material distribution
  13. An improved tabu search algorithm for solving heterogeneous fixed fleet open vehicle routing problem with time windows
  14. Partial linear recharging strategy for the electric fleet size and mix vehicle routing problem with time windows and recharging stations
  15. Energy efficient data transmission in intelligent transportation system (ITS): Millimeter (mm wave) based routing algorithm for connected vehicles
  16. Efficient and trusted autonomous vehicle routing protocol for 6G networks with computational intelligence
  17. A novel multi-objective optimization model for the vehicle routing problem with drone delivery and dynamic flight endurance
  18. PAAD (Partially adaptive and deterministic routing): A deadlock free congestion aware hybrid routing for 2D mesh network-on-chips.
  19. Branch-and-cut-and-price for the Electric Vehicle Routing Problem with Time Windows, Piecewise-Linear Recharging and Capacitated Recharging Stations
  20. Optimality analysis of train platforming and routing with different interlocking modes