A traffic generation model is a stochastic model of the traffic flows or data sources in a communication network, for example a cellular network or a computer network. A packet generation model is a traffic generation model of the packet flows or data sources in a packet-switched network. For example, a web traffic model is a model of the data that is sent or received by a user's web-browser. These models are useful during the development of telecommunication technologies, in view to analyse the performance and capacity of various protocols, algorithms and network topologies .
The network performance can be analyzed by network traffic measurement in a testbed network, using a network traffic generator such as iperf, bwping and Mausezahn. The traffic generator sends dummy packets, often with a unique packet identifier, making it possible to keep track of the packet delivery in the network.
Numerical analysis using network simulation is often a less expensive approach.
An analytical approach using queueing theory may be possible for a simplified traffic model but is often too complicated if a realistic traffic model is used.
The greedy source modeledit
A simplified packet data model is the greedy source model. It may be useful in analyzing the maximum throughput for best-effort traffic (without any quality-of-service guarantees). Many traffic generators are greedy sources.
Poisson traffic modeledit
Another simplified traditional traffic generation model for packet data, is the Poisson process, where the number of incoming packets and/or the packet lengths are modeled as an exponential distribution. When the packets interarrival time is exponential, with constant packet size it resembles an M/D/1 system. When both packet inter arrivals and sizes are exponential, it is an M/M/1 queue:[1]
The actual content of the payload data is typically not modeled, but replaced by dummy packets. However, if the payload data is to be analyzed on the receiver side, for example regarding bit-error rate, a Bernoulli process is often assumed, i.e. a random sequence of independent binary numbers. In this case, a channel model reflects channel impairments such as noise, interference and distortion.
3GPP2 modeledit
One of the 3GPP2 models is described in.[2] This document describes the following types of traffic flows:
The main idea is to partly implement HTTP, FTP and TCP protocols. For example, an HTTP traffic generator simulates the download of a web-page, consisting of a number of small objects (like images). A TCP stream (that's why TCP generator is a must in this model) is used to download these objects according to HTTP1.0 or HTTP1.1 specifications. These models take into account the details of these protocols' work. The Voice, WAP and Mobile Network Gaming are modelled in a less complicated way.
^CDMA2000 Evaluation Methodology Version 1.0 (Revision 0) 2006-10-14 at the Wayback Machine
November 29, 2023
traffic, generation, model, this, article, needs, additional, citations, verification, please, help, improve, this, article, adding, citations, reliable, sources, unsourced, material, challenged, removed, find, sources, news, newspapers, books, scholar, jstor,. This article needs additional citations for verification Please help improve this article by adding citations to reliable sources Unsourced material may be challenged and removed Find sources Traffic generation model news newspapers books scholar JSTOR May 2013 Learn how and when to remove this template message A traffic generation model is a stochastic model of the traffic flows or data sources in a communication network for example a cellular network or a computer network A packet generation model is a traffic generation model of the packet flows or data sources in a packet switched network For example a web traffic model is a model of the data that is sent or received by a user s web browser These models are useful during the development of telecommunication technologies in view to analyse the performance and capacity of various protocols algorithms and network topologies Contents 1 Application 2 The greedy source model 3 Poisson traffic model 4 Long tail traffic models 5 Payload data model 5 1 3GPP2 model 6 See also 7 ReferencesApplication editThe network performance can be analyzed by network traffic measurement in a testbed network using a network traffic generator such as iperf bwping and Mausezahn The traffic generator sends dummy packets often with a unique packet identifier making it possible to keep track of the packet delivery in the network Numerical analysis using network simulation is often a less expensive approach An analytical approach using queueing theory may be possible for a simplified traffic model but is often too complicated if a realistic traffic model is used The greedy source model editA simplified packet data model is the greedy source model It may be useful in analyzing the maximum throughput for best effort traffic without any quality of service guarantees Many traffic generators are greedy sources Poisson traffic model editAnother simplified traditional traffic generation model for packet data is the Poisson process where the number of incoming packets and or the packet lengths are modeled as an exponential distribution When the packets interarrival time is exponential with constant packet size it resembles an M D 1 system When both packet inter arrivals and sizes are exponential it is an M M 1 queue 1 Long tail traffic models editHowever the Poisson traffic model is memoryless which means that it does not reflect the bursty nature of packet data also known as the long range dependency For a more realistic model a self similar process such as the Pareto distribution can be used as a long tail traffic model Payload data model editThe actual content of the payload data is typically not modeled but replaced by dummy packets However if the payload data is to be analyzed on the receiver side for example regarding bit error rate a Bernoulli process is often assumed i e a random sequence of independent binary numbers In this case a channel model reflects channel impairments such as noise interference and distortion 3GPP2 model edit One of the 3GPP2 models is described in 2 This document describes the following types of traffic flows Downlink HTTP TCP FTP TCP Wireless Application Protocol near real time Video Voice Uplink HTTP TCP FTP TCP Wireless Application Protocol Voice Mobile Network GamingThe main idea is to partly implement HTTP FTP and TCP protocols For example an HTTP traffic generator simulates the download of a web page consisting of a number of small objects like images A TCP stream that s why TCP generator is a must in this model is used to download these objects according to HTTP1 0 or HTTP1 1 specifications These models take into account the details of these protocols work The Voice WAP and Mobile Network Gaming are modelled in a less complicated way See also editChannel model Measuring network throughput Mobility model Network emulation Network traffic simulation Network simulation Radio propagation model Queueing theory Packet generator Packet snifferReferences edit M D 1 M M 1 and M G 1 queuing PDF CDMA2000 Evaluation Methodology Version 1 0 Revision 0 Archived 2006 10 14 at the Wayback Machine Retrieved from https en wikipedia org w index php title Traffic generation model amp oldid 1120145587, wikipedia, wiki, book, books, library,
