Temat: background traffic - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Background Traffic Simulator - The Tool for WLAN Background Traffic Generation in ns-3 Environment
Autorzy:: Stryczek, Szymon
Gwiazdowicz, Mikołaj
Natkaniec, Marek
Powiązania:: https://bibliotekanauki.pl/articles/2203000.pdf
Data publikacji:: 2023
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: background traffic
ns-3
simulator
traffic generation
WLAN
Opis:: In the paper, the BTS (Background Traffic Simulator) tool is proposed to capture network traffic and then reproduce it in a simulations using the ns-3 simulator extension module. This new method of generating background traffic allows for repetitive testing of simulation scenarios under real network conditions. The authors described the differences between the previously available methods and the proposed solution. The operation of all the most important elements of the proposed tool has been described. The influence of the generated background traffic on the simulation scenario was presented as well as the results of the operation.
Źródło:: International Journal of Electronics and Telecommunications; 2023, 69, 1; 177--183
2300-1933
Pojawia się w:: International Journal of Electronics and Telecommunications
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Detailed evaluation and analysis of vision-based online traffic parameters estimation approach using low resolution web cameras
Autorzy:: Ali, M.
Touko Tcheumadjeu, L.
Zuev, S.
Ruppe, S.
Powiązania:: https://bibliotekanauki.pl/articles/393806.pdf
Data publikacji:: 2014
Wydawca:: Polskie Stowarzyszenie Telematyki Transportu
Tematy:: background estimation
vehicle detection
time mean speed
traffic flow
traffic state
classification
estymacja tła
detekcja pojazdu
płynność ruchu
stan ruchu
klasyfikacja
Opis:: In this paper, we give an overview and a detail analysis of our approach for vision-based real-time traffic parameters estimation using low-resolution web cameras. Traffic parameters estimation approach mainly includes three major steps, (1) stable background estimation, (2) vehicle detection, mean speed and traffic flow estimation, and (3) traffic scene classification into three states (normal and congested). The background image is estimated and updated in realtime by novel background estimation algorithm based on the median of First-in-First-Out (FIFO) buffer of rectified traffic images. Vehicles are detected by background subtraction followed by post-processing steps. By exploiting the domain knowledge of real-world traffic flow patterns, mean speed and traffic flow can be estimated reliably and accurately. Naive Bayes classifier with statistical features is used for traffic scene classification. The traffic parameter estimation approach is tested and evaluated at the German Aerospace Center’s (DLR) urban road research laboratory in Berlin for 24 hours of live streaming data from web-cameras with frames per second 1, 5 and 10. Image resolution is 348 x 259 and JPEG compression is 50%. Processed traffic data is cross-checked with synchronized induction loop data. Detailed evaluation and analysis shows high accuracy and robustness of traffic parameters estimation approach using low-resolution web-cameras under challenging traffic conditions.
Źródło:: Archives of Transport System Telematics; 2014, 7, 2; 9-13
1899-8208
Pojawia się w:: Archives of Transport System Telematics
Dostawca treści:: Biblioteka Nauki

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