This article needs additional citations for verification. Please help improve book business model generation pdf article by adding citations to reliable sources.
Unsourced material may be challenged and removed. 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 analysed 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 simplified traffic model, but is often too complicated if a realistic traffic model is used.
A simplified packet data model is the greedy source model. Many traffic generators are greedy sources. Another simplified traditional traffic generation model for circuit-switched data as well as packet data, is the Poisson process, where the number of incoming packets or calls per time unit follows the Poisson distribution. The length of each phone call is typically modelled as an exponential distribution.
The number of simultaneously ongoing phone calls follows the Erlang distribution. However, the Poisson traffic model is memoryless, which means that is 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. The actual content of the payload data is typically not modelled, 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. In this case a channel model reflects channel impairments such as noise, interference and distortion. There are at least two standardized traffic generation models for packet-switched wireless networks: the 3GPP2 model and the 802.
The 3GPP2 model is much more complex to implement but it is supposed to give more precise results. 16 model is much simpler in realization. The 3GPP2 model is described in. The main idea is to partly implement HTTP, FTP and TCP protocols.