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Jamming Detection in Electromagnetic Communication with Machine Learning: A Survey and Perspective
Published in Kim Phuc Tran, Machine Learning and Probabilistic Graphical Models for Decision Support Systems, 2023
Jonathan Villain, Virginie Deniau, Christophe Gransart
For the experiments, a specific Wi-Fi network was set-up in a room of the university Gustave Eiffel by installing a server, an access point and a client computer. The client computer is equipped with the Iperf network testing tool. Iperf allows creating TCP and UDP data streams and measuring the network throughput. The Wi-Fi channel employed is centered on the 2.422 GHz frequency. The jamming signal is emitted with a small omni-directional antenna connected to the arbitrary waveform generator and the attenuation control unit. The variable attenuation control unit allows adjusting the jamming signal power. We measured the bit rate thanks to the Iperf software, and we increased progressively the power of the jamming signal until we observed a very small impact on the bit rate.
Semantic driven code generation for networking testbed experimentation
Published in Enterprise Information Systems, 2018
Filip Jelenkovic, Milorad Tosic, Valentina Nejkovic
Because our experiment topology consists of five nodes (named Grape, Apple, Plum, Lemon and Orange), we assign two nodes to run iperf server (Lemon and Orange), and three nodes to run iperf client (Grape, Apple and Plum). One server is connected to the clients via fast link (Lemon), and the other server has slow link (Orange). Slow link is simulated by limiting the throughput of the network interface using wondershaper (WonderShaper, 2001) application. One of the client nodes (Apple) is used for the throughput measurement of each of the servers. The results of the measurements are uploaded to SecGENE server. SecGENE server analyses the results, using appropriate ontology, and concludes what server has the best throughput. The information about the best server is sent to the second client node (Grape) which is a client coordinated by SecGENE server to find the best server to communicate with. The third client node is a non-coordinated client (Plum). It does not know what the best server is and randomly chooses one of them. The coordinated client performs 16 data transfers and records the throughput. The non-coordinated client also performs 16 data transfers, but in a different way. It randomly chooses a server and performs 4 data transfers. Then, it again randomly chooses a server and performs 4 data transfer. In total, it randomly chooses server 4 times and performs 4 data transfers with each server. The results are given in Figure 14. It can be seen that the coordinated user always uses the best server, whereas the non-coordinated user uses slower server for 50% of time.