Context-aware Hybrid Adaptive Beaconing for Driver Behavior Dissemination in VANETs

Chhabra, Rishu; Krishna, C. Rama; Verma, Seema

doi:10.1080/03772063.2021.1941329

Cited by 11 publications

(5 citation statements)

References 35 publications

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“…In this probabilistic Manhattan grid topology, vehicles traverse both horizontal and vertical streets in their designated lanes. At intersections between horizontal and vertical roads, vehicles follow a specific probability distribution 20 . While this probabilistic method may not be suitable for highway systems, it offers a flexible means of altering the direction of vehicular nodes and upholds geographical constraints on vehicular node mobility.…”

Section: Proposed Methodologymentioning

confidence: 99%

Traffic coordination by reducing jamming attackers in VANET using probabilistic Manhattan Grid Topology for automobile applications

Santhi,

Jacob,

Sheela

et al. 2024

Sci Rep

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In recent years Intelligent Transportation System (ITS) has been growing interest in the development of vehicular communication technology. The traffic in India shows considerable fluctuations owing to the static and dynamic characteristics of road vehicles in VANET (Vehicular Adhoc Network). These vehicles take up a convenient side lane position on the road, disregarding lane discipline. They utilize the opposing lane to overtake slower-moving vehicles, even when there are oncoming vehicles approaching. The primary objective of this study is to minimize injuries resulting from vehicle interactions in mixed traffic conditions on undivided roads. This is achieved through the implementation of the Modified Manhattan grid topology, which primarily serves to guide drivers in the correct path when navigating undivided roads. Furthermore, the Fuzzy C-Means algorithm (FCM) is applied to detect potential jamming attackers, while the Modified Fisheye State Routing (MFSR) Algorithm is employed to minimize the amount of information exchanged among vehicles. Subsequently, the Particle Swarm Optimization (PSO) algorithm is developed to enhance the accuracy of determining the coordinates of jamming attackers within individual clusters. The effectiveness of the outcomes is affirmed through the utilization of the Fuzzy C-Means algorithm, showcasing a notable 30% reduction in the number of attackers, along with the attainment of a 70% accuracy rate in this research endeavor.

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Section: Proposed Methodologymentioning

confidence: 99%

Traffic coordination by reducing jamming attackers in VANET using probabilistic Manhattan Grid Topology for automobile applications

Santhi,

Jacob,

Sheela

et al. 2024

Sci Rep

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show abstract

“…A context-aware hybrid beaconing algorithm is proposed in [28], aiming to enhance safety by disseminating driver status via beacons to neighboring vehicles in IEEE 802.11pbased networks. The comprehensive context is taken into account to derive driver status and initial network status.…”

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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“…A joint power and rate algorithm in [ 20 ], which can set different priorities for different vehicles, introduces fairness into V2V communication, and conducts simulation verification through multiple scenarios. In [ 21 ], the authors propose a perception-based hybrid beacon algorithm that utilizes the driver’s state as a reference condition and broadcasts it to nearby vehicles, then makes joint decisions to adjust the transmission range and power in order to enhance safety. In [ 22 ], the authors propose an approach that integrates real-time traffic flow sensing with channel congestion status, utilizing distributed network utility maximization to improve channel utilization.…”

Section: Related Workmentioning

confidence: 99%

A Hybrid Power-Rate Management Strategy in Distributed Congestion Control for 5G-NR-V2X Sidelink Communications

Tian

Islam

et al. 2023

Sensors

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The accelerated growth of 5G technology has facilitated substantial progress in the realm of vehicle-to-everything (V2X) communications. Consequently, achieving optimal network performance and addressing congestion-related challenges have become paramount. This research proposes a unique hybrid power and rate control management strategy for distributed congestion control (HPR-DCC) focusing on 5G-NR-V2X sidelink communications. The primary objective of this strategy is to enhance network performance while simultaneously preventing congestion. By implementing the HPR-DCC strategy, a more fine-grained and adaptive control over the transmit power and transmission rate can be achieved. This enables efficient control by dynamically adjusting transmission parameters based on the network conditions. This study outlines the system model and methodology used to develop the HPR-DCC algorithm and investigates its characteristics of stability and convergence. Simulation results indicate that the proposed method effectively controls the maximum CBR value at 64% during high congestion scenarios, which leads to a 6% performance improvement over the conventional DCC approach. Furthermore, this approach enhances the signal reception range by 20 m, while maintaining the 90% packet reception ratio (PRR). The proposed HPR-DCC contributes to optimizing the quality and reliability of 5G-NR-V2X sidelink communication and holds great promise for advancing V2X applications in intelligent transportation systems.

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Context-aware Hybrid Adaptive Beaconing for Driver Behavior Dissemination in VANETs

Cited by 11 publications

References 35 publications

Traffic coordination by reducing jamming attackers in VANET using probabilistic Manhattan Grid Topology for automobile applications

Traffic coordination by reducing jamming attackers in VANET using probabilistic Manhattan Grid Topology for automobile applications

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

A Hybrid Power-Rate Management Strategy in Distributed Congestion Control for 5G-NR-V2X Sidelink Communications

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