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Mausezahn (German pronunciation: [ˈmaʊ̯zəˌʦaːn], German for "mouse tooth") is a fast network traffic generator written in C which allows the user to craft nearly every possible and "impossible" packet. Since version 0.31 Mausezahn is open source in terms of the GPLv2.
A non-routing node in promiscuous mode can generally only monitor traffic to and from other nodes within the same collision domain (for Ethernet and IEEE 802.11) or ring (for Token Ring). Computers attached to the same Ethernet hub satisfy this requirement, which is why network switches are used to combat malicious use of promiscuous mode.
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.
An SD-WAN utilizing virtualization techniques assisted with WAN Optimization traffic control allows network bandwidth to dynamically grow or shrink as needed. SD-WAN technology and WAN optimization can be used separately or together, [ 30 ] and some SD-WAN vendors are adding WAN optimization features to their products.
This is done because network intrusion detection software cannot as easily find instances of malicious network traffic when it is mixed in with non-malicious network traffic generated by legitimate users of the network. [9] The traffic generators used by the testbed run on a modified version of Linux, [10] and a Java-based [10] graphical user ...
A packet generator or packet builder is a type of software that generates random packets or allows the user to construct detailed custom packets. Depending on the network medium and operating system, packet generators utilize raw sockets , NDIS function calls, or direct access to the network adapter kernel-mode driver .
Network emulation is a technique for testing the performance of real applications over a virtual network. This is different from network simulation where virtual models of traffic, network models, channels, and protocols are applied. The aim is to assess performance, predict the impact of change, or otherwise optimize technology decision-making.
Network traffic simulation usually follows the following four steps: [1] [2] Modelling the system as a dynamic stochastic (i.e. random) process; Generation of the realizations of this stochastic process; Measurement of Simulation data; Analysis of output data
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