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A priority-based congestion control algorithm for on-road traffic in smart cities.
Tshilongamulenzhe, Ndivhuho
Tshilongamulenzhe, Ndivhuho
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Abstract
The concept of wireless sensor networks (WSNs) has generated significant attention on a global scale. According to the IEEE 802.11 standard, WSNs are wireless networks composed of sensor nodes (SNs) that interconnect via wireless links. SNs can sense, process, and communicate wirelessly in a harsh environment. WSNs are primarily used for traffic communication in a wide range of environments such as smart cities, healthcare, homes, and military areas. The implementation of WSNs in various environments such as smart cities comes with various challenges, such as traffic congestion. The traffic congestion that occurs on the roads within a smart city during peak hours is normally caused by numerous vehicles travelling at the same time. As a result, traffic jams, time delays, and accidents occur during traffic congestion under varying weather conditions, whether sunny or rainy. This research study proposed a new algorithm called the priority-based congestion control (PBCC) algorithm, which is designed by integrating the fusion-based intelligent traffic congestion control (FITCC) algorithm and traffic congestion detection (TCD) in order to reduce on-road traffic congestion within smart cities. This research study used Network Simulator 3 (NS-3) to evaluate the effectiveness of the proposed PBCC algorithm compared with the FITCC and the TCD algorithms. During sunny days, the NS-3 simulation results demonstrated that the proposed PBCC algorithm has an average of a 0.83% false alarm rate (FAR), a 76.0% mean time to detection (MTTD), and an 84.3% detection rate (DR) improvement over the FITCC and the TCD. The NS-3 simulation results during rainy days demonstrated that the proposed PBCC algorithm has an average of 14.09% FAR, 57.03% MMTD, and 78.04% DR improvement over the FITCC and the TCD within smart cities.
Description
Master of Computing: Information Technology in the Department of Information Technology Faculty of Information and Communication Technology at the Tshwane University of Technology.
Date
2025-02-01
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Tshwane University of Technology
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Keywords
Traffic congestion., WSNs., Network simulator 3., Traffic congestion detection., Fusion-based intelligent traffic congestion control., Priority-based congestion control.
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License
CC0 1.0 Universal