Modeling and Tools for Network Simulation

Modeling and Tools for Network Simulation

A broad scope of concepts from cultural data networks to evolving regions such as software-defined networking (SDN) and Internet of Things (IoT) are extended by the projects that are utilizing these tools. Among different concepts, the following are project ideas employing simulation tools and network modelling:

Traditional and Wireless Networking

  • Performance Analysis of Routing Protocols: By employing GNS3 or NS-3, contrast cultural routing protocols such as EIGRP, OSPF, and wireless routing protocols like DSR, AODV under various network situations.
  • Wi-Fi 6 Deployment Scenarios: To assess effectiveness enhancements and find best arrangement scenarios, aim to simulate the implementation of Wi-Fi 6 also known as 802.11ax in different platforms such as campuses, offices.

Internet of Things (IoT)

  • IoT Network Scalability: Concentrating on parameters such as latency, packet loss, and throughput, it is approachable to employ NS-3 or OMNeT++ to simulate an IoT network with thousands of devices and examine the scalability of the network.
  • Energy Efficiency in IoT Networks: In order to research energy utilization and battery life enhancement policies, design IoT networks by utilizing low-power wide-area network (LPWAN) mechanisms like NB-IoT, LoRaWAN.

Software-Defined Networking (SDN) and Network Functions Virtualization (NFV)

  • SDN-Based Traffic Engineering: To model an SDN network by deploying custom traffic engineering methods for adapting to differing traffic trends in a dynamic manner, this project employs Mininet.
  • NFV Performance Benchmarks: By employing GNS3 or EstiNet, simulate virtualized network functions (NFVs) in a cloud data center to assess effectiveness, influence and resource consumption.

Cybersecurity

  • Simulating Cyber Attacks and Defenses: Examining the performance of different protection policies, employ NS-3 or GNS3 to simulate network assaults such as man-in-the-middle, DDoS, and deploy protective approaches.
  • Blockchain for Secure Network Communications: A blockchain-related secure interaction protocol has to be designed in OMNeT++ to evaluate its feasibility and effectiveness contrasted to cultural safety approaches.

5G and Beyond

  • 5G Network Slicing for Different Use Cases: Assessing in what way various slices can assist various necessities such as URLLC, mMTC, and eMBB, focus on using NS-3 with its 5G module to simulate network slicing mechanism.
  • Performance Evaluation of 5G mmWave Communications: To simulate mmWave interactions in a 5G network, utilize NS-3 by concentrating on limitations such as high obstruction and attenuation, and thereby suggesting reduction policies.

Smart Cities and Vehicular Networks

  • Vehicular Ad-Hoc Networks (VANETs) for Smart Traffic Management: Particularly, to assess in what way actual time data exchange among vehicles can enhance congestion flow and security, simulate a VANET employing OMNeT++ and Veins model.
  • Smart Grid Communication Networks: Examining the consistency and delay of various interaction mechanisms assisting grid functions, aim to design a smart grid communication network by utilizing NS-3.

Satellite Communications

  • Low Earth Orbit (LEO) Satellite Networks for Global Internet Coverage: To simulate LEO satellite constellations, it is beneficial to make use of NS-3 or STK (System Tool Kit) by exploring delay, coverage, and handover policies for universal internet service provision.

What are some good simulation tools to simulate an IoT based project?

    There are numerous simulation tools, but some are considered as efficient and suitable to simulate an IoT based project. We offer few extensively utilized simulation tools that are appropriate for IoT projects, together with their major characteristics:

  1. OMNeT++
  • Major Characteristics: Specifically, OMNeT++ is employed for constructing network simulators. It is a modular, extensible, component-related C++ simulation model and library. Along with its INET model, it assists a broad scope of protocols and principles that are helpful for IoT simulations encompassing wireless and mobile networks.
  • Appropriate for: It is mainly useful for simulating complicated IoT settings including different interaction mechanisms. In addition, OMNeT++ is suitable for projects that need extensive designing of network protocols and adaptability.
  1. NS-3 (Network Simulator 3)
  • Major Characteristics: For study and advancement, NS-3 is extensively employed in educational and business domains. Generally, NS-3 is a discrete-event network simulator that is familiar for its strength and assists in simulating a broad range of network mechanisms such as Bluetooth, Wi-Fi, LTE, and more, that are related for IoT.
  • Appropriate for: Specifically, for projects that concentrate on wireless communication factors of IoT and research-based IoT projects that require high reliability in simulation outcomes, this tool is considered as most suitable.
  1. Cooja / Contiki
  • Major Characteristics: Cooja permits for the simulation of IoT devices executing the Contiki operating system. It is the default simulator for the Contiki OS. Typically, it assists co-simulation of simulated as well as actual hardware nodes and has the capability to simulate extensive networks of interrelated devices.
  • Appropriate for: The Cooja/Contiki simulation tool is appropriate for projects that are aimed to execute on resource-limited devices and concentrates on the advancement and examining of IoT firmware and applications.
  1. IoTify
  • Major Characteristics: To simulate different IoT application areas such as smart city, smart home, and industrial IoT applications, IoTify offers an adaptable platform. It is a cloud-related network simulation that permits the virtual designing of IoT devices and networks.
  • Appropriate for: Mainly, when easy utilization and rapid arrangement are examined as precedence, this tool is suitable for fast modelling and examining of IoT applications in a cloud platform.
  1. MATLAB and Simulink
  • Major Characteristics: For simulating and examining IoT frameworks, encompassing sensor networks, data analytics, and wireless communications, MATLAB and Simulink provide widespread toolboxes. Specifically, for algorithm advancement, data exploration, and visualization, MATLAB offers a robust platform.
  • Appropriate for: Typically, this tool is perfect for interdisciplinary IoT projects that incorporate interactions, control frameworks, and analytics. In addition, it is appropriate for projects that need complicated data exploration, system designing, or signal processing.
  1. Mininet-IoT
  • Major Characteristics: To simulate different network situations and device kinds, Mininet-IoT assists the simulation of IoT networks with characteristics. Generally, Mininet-IoT is determined as an expansion of Mininet. It combines with the SDN controller in an efficient manner, thereby making it appropriate for testing with SDN-related IoT networks.
  • Appropriate for: The Mininet-IoT simulation tool is suitable for projects investigating SDN applications encompassing network management and safety factors.
  1. NetSim
  • Major Characteristics: NetSim presents a thorough library of network protocols and device frameworks. It is an extensive network simulation tool that provides specific assistance to IoT protocols such as Zigbee, MQTT, and CoAP, among others.
  • Appropriate for: With a concentration on network consistency and scalability, this tool is best for IoT projects needing complete protocol exploration and performance assessment.
Network Modelling And Simulation Tools topics

Network Modelling and Simulation Tools Projects

It’s crucial to wrap up the tool selection process before diving into your project. We understand that there are numerous networking tools out there, and we’re here to assist scholars in finding the perfect fit for their projects. Below, you’ll find a compilation of our  most popular Network Modelling and Simulation Tools Projects that are currently trending among scholars.

  1. Adversarial Deep Learning approach detection and defense against DDoS attacks in SDN environments
  2. SYNCOP: An evolutionary multi-objective placement of SDN controllers for optimizing cost and network performance in WSNs
  3. ByteSGAN: A semi-supervised Generative Adversarial Network for encrypted traffic classification in SDN Edge Gateway
  4. ADMS: An online attack detection and mitigation system for LDoS attacks via SDN
  5. Resilient backup controller placement in distributed SDN under critical targeted attacks
  6. Mobile-edge computing-based delay minimization controller placement in SDN-IoV
  7. When SDN meets C-RAN: A survey exploring multi-point coordination, interference, and performance
  8. Joint optimization of primary and backup controller placement and availability link upgrade in SDN networks
  9. Linking handover delay to load balancing in SDN-based heterogeneous networks
  10. A hierarchical approach for accelerating IoT data management process based on SDN principles
  11. A DDoS attack detection and defense scheme using time-series analysis for SDN
  12. Towards trusted and efficient SDN topology discovery: A lightweight topology verification scheme
  13. Adaptive distributed SDN controllers: Application to Content-Centric Delivery Networks
  14. FCNR: Fast and Consistent Network Reconfiguration with low latency for SDN
  15. Ob-EID: Obstacle aware event information dissemination for SDN enabled vehicular network
  16. Improving dynamic service function chaining classification in NFV/SDN networks through the offloading concept
  17. Fault tolerance in SDN data plane considering network and application based metrics
  18. SARSA-based delay-aware route selection for SDN-enabled wireless-PLC power distribution IoT
  19. Packet-in request redirection: A load-balancing mechanism for minimizing control plane response time in SDNs
  20. Experimental validation of an SDN residential network management proposal over a GPON testbed
Live Tasks
Technology Ph.D MS M.Tech
NS2 75 117 95
NS3 98 119 206
OMNET++ 103 95 87
OPNET 36 64 89
QULANET 30 76 60
MININET 71 62 74
MATLAB 96 185 180
LTESIM 38 32 16
COOJA SIMULATOR 35 67 28
CONTIKI OS 42 36 29
GNS3 35 89 14
NETSIM 35 11 21
EVE-NG 4 8 9
TRANS 9 5 4
PEERSIM 8 8 12
GLOMOSIM 6 10 6
RTOOL 13 15 8
KATHARA SHADOW 9 8 9
VNX and VNUML 8 7 8
WISTAR 9 9 8
CNET 6 8 4
ESCAPE 8 7 9
NETMIRAGE 7 11 7
BOSON NETSIM 6 8 9
VIRL 9 9 8
CISCO PACKET TRACER 7 7 10
SWAN 9 19 5
JAVASIM 40 68 69
SSFNET 7 9 8
TOSSIM 5 7 4
PSIM 7 8 6
PETRI NET 4 6 4
ONESIM 5 10 5
OPTISYSTEM 32 64 24
DIVERT 4 9 8
TINY OS 19 27 17
TRANS 7 8 6
OPENPANA 8 9 9
SECURE CRT 7 8 7
EXTENDSIM 6 7 5
CONSELF 7 19 6
ARENA 5 12 9
VENSIM 8 10 7
MARIONNET 5 7 9
NETKIT 6 8 7
GEOIP 9 17 8
REAL 7 5 5
NEST 5 10 9
PTOLEMY 7 8 4

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