Network simulation: Difference between revisions

Revision as of 11:34, 4 July 2024

Latest revision as of 01:22, 17 August 2025

(15 intermediate revisions by 7 users not shown)

Line 10:

==Simulations==

Most of the commercial [[Simulation|simulators]] are [[GUI]] driven, while some network simulators are [[Command-line interface|CLI]] driven. The network model/configuration describes the network (nodes, routers, switches, links) and the events (data transmissions, packet error, etc.). Output results would include network-level metrics, link metrics, device metrics etc. Further, drill down in terms of simulations [[tracing (software)|trace]] files would also be available. Trace files log every packet, every event that occurred in the simulation and is used for analysis. Most network simulators use [[discrete event simulation]], in which a list of pending "events" is stored, and those events are processed in order, with some events triggering future events—such as the event of the arrival of a packet at one node triggering the event of the arrival of that packet at a [[Downstream (networking)|downstream]] node.<section end=transclusionLabelG20170307T1400GMT1 />

==Network emulation==

Line 25:

* [[GloMoSim]]

There are also some notable closed sourcecommercial network simulators. These include:

*OPNET (Riverbed)

*NetSim (Tetcos)

==Uses of network simulators ==

Network simulators provide a cost-effective method for

* 5G-NR, 6G, NTN coverage, capacity, throughput and latency analysis

* Network R & D (More than 70% of all Network [[Academic paper|Research paper]] reference a network simulator)

* Defense applications such as [[High frequency|HF]] / [[UHF]] / [[VHF]]/L-Band Radio based [[MANET]] Radios, [[TacticalDynamic dataTDMA link]]sMAC, PHY Waveforms etc.

* [[Internet of things|IOT]], [[VANET]] simulations

* [[Unmanned aerial vehicle|UAV]] network/[[wikt:drone|drone]] swarm communication simulation

* [[Machine Learning]]: Testing ML algorithms for optimizing network parameters, generating synthetic data training ML algorithms oncommunication networks

* Education: Online courses, Lab experimentation, and R & D. Most universities use a network simulator for teaching / R & D since it is too expensive to buy hardware equipment

Line 45 ⟶ 42:

* Model the [[network topology]] specifying the nodes on the network and the links between those nodes

* Model the application flow (traffic) between the nodes

* Providing network performance metrics such as throughput, latency, error, etc., as output

* Technology/protocolEvaluate evaluationprotocol and device designs

* Visualization of the packet flow

* LoggingLog ofradio measurements, packet/ and events for drill-down analyses/ and debugging

* Technology/protocol evaluation and device designs

* Logging of packet/events for drill-down analyses/debugging

==See also==