Several SDN-based simulation tools have emerged that are employed in an extensive manner for various purposes. If you want tailored services on SDN-based simulation then will be your trusted partner. Including the relevant parameters and protocols, we list out a few prominent SDN simulation tools to consider: 

  1. Mininet

For the process of simulating a virtual network, Mininet is one of the highly employed tools, which executes actual kernel, application code, and switch. To model SDN applications, it is considered as more efficient.

  • Protocols: P4, OVSDB (Open vSwitch Database Management Protocol), and OpenFlow.
  • Potential Parameters: It includes controller link information, number of hosts, switches, topology varieties (such as custom, linear, and tree), CPU challenge, link bandwidth, loss, and delay.
  1. NS-3

NS-3 is referred to as a discrete-event network simulator.  For simulating IP and non-IP networks involving SDN platforms, this simulator is widely utilized in industrial and educational sectors.  

  • Protocols: Different IP protocols, SNMP, OpenFlow, HTTP, and MQTT.
  • Potential Parameters: Some of the significant parameters are packet loss, data rates, traffic models, network topology, delay, queue sizes, throughput, and others.
  1. OpenDaylight

OpenDaylight assists to simulate and handle SDN networks. It is generally specified as an open-source SDN controller environment. 

  • Protocols: OVSDB, OpenFlow, PCEP, BGP, NETCONF, and other major protocols.
  • Potential Parameters: Several network arrangements could be involved, such as node arrangements, network topology, policies, and flows.
  1. GNS3

GNS-3 stands for Graphical Network Simulator-3, which is capable of configuring complicated network topologies. It is termed as a network software emulator. For highly extensive simulations, GNS-3 can also be combined with SDN controllers in an efficient manner.

  • Protocols: GNS-3 can be merged with SDN controllers which employ OpenFlow protocol, and also enables various conventional networking protocols such as RIP, BGP, and OSPF.
  • Potential Parameters: Parameters encompasses diverse network configurations with various network protocols and contexts, VMs, switches, and routers.
  1. EstiNet

EStiNet specifically assists OpenFlow-related SDN simulation, and is examined as an industrial network simulation tool. 

  • Protocols: Supports different IP protocols and OpenFlow.
  • Potential Parameters: Elaborate network performance metrics, flow table arrangements, traffic generation, and network topology alteration could be included.

Simulation Setup Factors:

It is important to focus on the below specified aspects while configuring an SDN simulation:

  1. Network Topology: Initially, the design of your network has to be determined. Mesh, star, tree, or custom topologies outlined by the users are the general topologies encompassed in simulations.
  2. Traffic Generation: For interpreting in what way the network functions on the basis of different load constraints, simulate various kinds of network traffic.
  3. Controller Configuration: The appropriate SDN controller has to be arranged and configured. The entire activity of the network can be majorly affected by the performance of the controller.
  4. Performance Metrics: For your simulation, it is significant to choose relevant metrics like network resource consumption, latency, packet loss, and throughput.
  5. Scalability and Strength: On the basis of failure states or increased number of nodes, examine in what way the network functions.

What is the best open source network controller for software Defined networking SDN based on OpenFlow?

Numerous network controllers are there for software defined networking (SDN) relevant to OpenFlow. Based on the project requirements, the suitable controller has to be selected. The following are more prevalent open-source SDN-based controllers, which are generally related to OpenFlow protocol: 

  1. OpenDaylight (ODL)

In the industry, OpenDaylight is the extensively used and more powerful SDN controller. It assists diverse networking protocols such as OpenFlow and is considered as a joint initiative based on Linux infrastructure. OpenDaylight enables network handling, automation, and arrangements, because it is modeled as an adaptable and scalable controller.

  • Advantages: It has an extensive scalability, wide range of protocol assistance, and efficient committee support.
  • Application Areas: For complicated and broader networks such as service contributor, cloud data center platforms, and enterprise, OpenDaylight controller is highly appropriate.
  1. ONOS (Open Network Operating System)

Another top open-source SDN controller is ONOS. It is more ideal for highly robust networks, due to its extensive scalability and efficiency. It provides various important characteristics such as larger accessibility and scalability and also assists OpenFlow in addition to other protocols.

  • Advantages: ONOS enables various southbound protocols and has superior efficiency. It is majorly modeled for extensive accessibility.
  • Application Areas: Specifically for the contexts which need larger scalability and accessibility and for service contributors, this controller is highly suitable.
  1. Ryu

When compared to ONOS and OpenDaylight, Ryu is considered as a highly lightweight SDN controller, which is drafted in Python completely. For the developers who have expertise in Python, this controller is typically more accessible. Ryu enables the creation and placement of novel network management and control applications in a rapid manner, because it is completely flexible and assists all versions of OpenFlow. 

  • Advantages: It is more user-friendly because of Python usage, offers assistance for all versions of OpenFlow, and is examined as efficient for its transparency.
  • Application Areas: Major use cases include small-to-medium industrial networks, research, and academics.
  1. Floodlight

Floodlight is most prominent in small-scale industry and educational platforms, because it is very simple to employ and configure. It is referred to as an Apache-copyrighted SDN controller. It is capable of managing integrated OpenFlow and non-OpenFlow networks and enables different versions of OpenFlow.

  • Advantages: For small or medium-sized networks, Floodlight is highly appropriate. It is an open-source controller and can be utilized in an easier manner.
  • Application Areas: It is more suitable for academic objectives, small to medium-sized networks, and learners.

Aspects for Selecting an SDN Controller

Examine the major factors while choosing an SDN controller:  

  • Scalability: Does the controller efficiently scale with your network dimension?
  • Committee and Assistance: Is there any advancements and effective committee assistance? For troubleshooting and improvements, this can be most significant.
  • Compatibility: Does the controller enable the specific OpenFlow versions that are important for your network equipment?
  • Feature Set: Does it have all the major characteristics (like safety characteristics, API accessibility, and GUI), which are essential for your particular network specifications?
  • User-friendliness: It is crucial to examine the accessibility of documentation and learning curve for beginners.
SDN Simulation Topics

SDN Simulation Project Topics & Ideas is a reliable source for innovative SDN Simulation, offering a range of cutting-edge SDN Project Topics & Ideas to spark inspiration.Read some of the intruging ideas that are listed below.

  1. Congestion-aware local reroute for fast failure recovery in software-defined networks
  2. Advanced support vector machine-(ASVM-) based detection for distributed denial of service (DDoS) attack on software defined networking (SDN)
  3. Achieving DDoS resiliency in a software defined network by intelligent risk assessment based on neural networks and danger theory
  4. Towards improving resilience of controller placement with minimum backup capacity in software defined networks
  5. Service chain embedding with maximum flow in software defined network and application to the next-generation cellular network architecture
  6. Payload-based traffic classification using multi-layer lstm in software defined networks
  7. Software-defined networking: Experimenting with the control to forwarding plane interface
  8. Software defined networking for next generation converged metro-access networks
  9. A multi-criteria-based DDoS-attack prevention solution using software defined networking
  10. Optical packet and circuit integrated networks and software defined networking extension
  11. A novel load balancing algorithm for software defined network based datacenters
  12. BWManager: Mitigating denial of service attacks in software-defined networks through bandwidth prediction
  13. TEDP: An enhanced topology discovery service for software-defined networking
  14. ECOS: Leveraging software-defined networks to support mobile application offloading
  15. Joint optimization of rule placement and traffic engineering for QoS provisioning in software defined network
  16. Optimal model for failure foresight capacitated controller placement in software-defined networks
  17. Flow based anomaly detection in software defined networking: A deep learning approach with feature selection method
  18. Adaptive load balancing scheme for data center networks using software defined network
  19. Suspicious flow forwarding for multiple intrusion detection systems on software-defined networks
  20. A novel hybrid flow-based handler with DDoS attacks in software-defined networking
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
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
RTOOL 13 15 8
VNX and VNUML 8 7 8
WISTAR 9 9 8
CNET 6 8 4
ESCAPE 8 7 9
VIRL 9 9 8
SWAN 9 19 5
JAVASIM 40 68 69
SSFNET 7 9 8
TOSSIM 5 7 4
PSIM 7 8 6
ONESIM 5 10 5
DIVERT 4 9 8
TINY OS 19 27 17
TRANS 7 8 6
CONSELF 7 19 6
ARENA 5 12 9
VENSIM 8 10 7
NETKIT 6 8 7
GEOIP 9 17 8
REAL 7 5 5
NEST 5 10 9

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