Adaptive Distributed Beacon Congestion Control with Machine Learning in VANETs

Mohammadi, Mahboubeh; Balador, Ali; Fernandez, Zaloa; Val, Iñaki

doi:10.1109/msn53354.2021.00120

Cited by 4 publications

(2 citation statements)

References 16 publications

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“…The study described in [26] introduces a beacon rate control technique based on link conditions. In that approach, nodes with a greater number of neighboring nodes are allocated a higher beacon rate.…”

Section: Related Workmentioning

confidence: 99%

Intelligent High-Awareness and Channel-Efficient Adaptive Beaconing Based on Density and Distribution for Vehicular Networks

Alhameed,

Mahgoub,

Limouchi

2024

Electronics

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In vehicle ad hoc networks (VANETs), a beacon is a periodic message sent to nearby vehicles containing essential details like the sender’s vehicle ID, location, speed, and direction. Maintaining the freshness of this information without causing network congestion requires adaptive beaconing to adjust to changes in mobility and network density. Our research, based on extensive simulation experiments, identifies specific parameter sets optimal for adapting beaconing rates to different scenarios. From this analysis, we introduce a novel scheme called high-awareness and channel-efficient adaptive beaconing (HACEAB), employing fuzzy logic to adapt to various environments and conditions. Initially, the protocol gauges network density using an adaptive threshold function, followed by estimating the node spatial distribution through the quadrat statistic method to discern uniform distribution or clustering. Utilizing these data, the protocol adjusts beaconing rates via appropriate input parameters for the fuzzy logic system. Remarkably, HACEAB represents the first beaconing scheme capable of simultaneously adjusting to changes in network density and spatial distribution. Furthermore, the protocol enhances performance by adapting transmission power to fluctuations in node density and distribution. NS-3 simulations validate the efficacy of these improvements.

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Section: Related Workmentioning

confidence: 99%

Intelligent High-Awareness and Channel-Efficient Adaptive Beaconing Based on Density and Distribution for Vehicular Networks

Alhameed,

Mahgoub,

Limouchi

2024

Electronics

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“…In Ref. [46], the authors assign a weight to each node based on quality of vehicle links and then use a greedy algorithm to assign suitable beacon rates to nodes based on the weights. In Ref.…”

Section: Power-and Message Rate-based Approachesmentioning

confidence: 99%

Data Rate Selection Strategies for Periodic Transmission of Safety Messages in VANET

St. Amour,

Jaekel

2023

Electronics

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Vehicular ad hoc networks (VANETs) facilitate communication among vehicles and possess designated infrastructure nodes to improve road safety and traffic flow. As the number of vehicles increases, the limited bandwidth of the wireless channel used for vehicle-to-vehicle (V2V) communication can become congested, leading to packets being dropped or delayed. VANET congestion control techniques attempt to address this by adjusting different transmission parameters, including the data rate, message rate, and transmission power. In this paper, we propose a decentralized congestion control algorithm where each factor adjusts the data rate (bitrate) used to transmit its wireless packet congestion based on the current load on the channel. The channel load is estimated independently by each vehicle using the measured channel busy ratio (CBR). The simulation results demonstrate that the proposed approach outperforms existing data rate-based algorithms, in terms of both packet reception and overall channel load.

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VANET Real Safety Congestion Control Wireless Access in Vehicular Environment Using Artificial Intelligence

Budholiya

Manwar

2023

2023 International Conference on Artificial Intelligence and Knowledge Discovery in Concurrent Engineering (ICECONF)

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Adaptive Distributed Beacon Congestion Control with Machine Learning in VANETs

Cited by 4 publications

References 16 publications

Intelligent High-Awareness and Channel-Efficient Adaptive Beaconing Based on Density and Distribution for Vehicular Networks

Intelligent High-Awareness and Channel-Efficient Adaptive Beaconing Based on Density and Distribution for Vehicular Networks

Data Rate Selection Strategies for Periodic Transmission of Safety Messages in VANET

VANET Real Safety Congestion Control Wireless Access in Vehicular Environment Using Artificial Intelligence

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