Roadside Unit Transmission Control for Energy Efficiency in Vehicle-to-Infrastructure Communication Network

Kouonchie, Paule Kevin Nembou; Oduol, Vitalice K.; Nyakoe, George N.

doi:10.14445/22315381/ijett-v70i5p217

Cited by 2 publications

(2 citation statements)

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“…is denoted by V2R/I. Vehicle-to-Infrastructure (V2I) communications are: Infrastructure-to-Infrastructure (I2I) and Infrastructure-to-Vehicle (I2V), these types of communication support longer distances within the network [19]. The Roadside Unit (RSU) together with V2V and V2I communications plays a vital role in providing services in the vehicle net-work, [20].…”

Section: Internet Of Vehicles and Communications In The Tra C Environ...mentioning

confidence: 99%

Modeling a LoRAWAN Network for Vehicle Wildlife Collision Avoidance System on Rural Roads

Jotanovic,

Jausevac,

Perakovic

et al. 2024

Preprint

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The network of rural roads covers different types of terrain, including forest areas, pastures, arable land and sparsely populated areas. The safety of people and animals is a priority in traffic on these roads. Early detection of pedestrians, animals and other moving objects along the road can significantly reduce the risk of accidents. As part of this research, a sensor system is being developed that can detect characteristics of living things in motion, such as unexpectedly crossing the road without clear signs. Such timely detection of moving objects enables adequate preventive measures and reduces potential traffic accidents. The consequences of traffic accidents of this type can cause serious damage to animals and people property, and road infrastructure. The topicality of this problem at the spatial and seasonal level is emphasized in studies that identify the hotspots of these accidents. Factors such as traffic characteristics and road infrastructure are key to modeling protective systems on rural roads. The presented study investigates the deployment of sensor nodes and LoRAWAN gateways for wildlife detection on rural roads, with the aim of reducing the risk of traffic accidents caused by Wildlife-Vehicle Collisions.

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Section: Internet Of Vehicles and Communications In The Tra C Environ...mentioning

confidence: 99%

Modeling a LoRAWAN Network for Vehicle Wildlife Collision Avoidance System on Rural Roads

Jotanovic,

Jausevac,

Perakovic

et al. 2024

Preprint

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show abstract

“…The QWLCPM scheme is positioned to take full advantage of emerging infrastructure enhancements, ensuring that it remains relevant and effective as vehicular networks evolve. This forward-looking approach ensures the scalability and adaptability of the scheme to future technological advancements [27]. A zone-based division facilitates the efficient and effective delivery of priority-based data.…”

Section: Zone Separationmentioning

confidence: 99%

QWLCPM: A Method for QoS-Aware Forwarding and Caching Using Simple Weighted Linear Combination and Proximity for Named Data Vehicular Sensor Network

Dhakal,

Sharma

2024

Electronics

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The named data vehicular sensor network (NDVSN) has become an increasingly important area of research because of the increasing demand for data transmission in vehicular networks. In such networks, ensuring the quality of service (QoS) of data transmission is essential. The NDVSN is a mobile ad hoc network that uses vehicles equipped with sensors to collect and disseminate data. QoS is critical in vehicular networks, as the data transmission must be reliable, efficient, and timely to support various applications. This paper proposes a QoS-aware forwarding and caching algorithm for NDVSNs, called QWLCPM (QoS-aware Forwarding and Caching using Weighted Linear Combination and Proximity Method). QWLCPM utilizes a weighted linear combination and proximity method to determine stable nodes and the best next-hop forwarding path based on various metrics, including priority, signal strength, vehicle speed, global positioning system data, and vehicle ID. Additionally, it incorporates a weighted linear combination method for the caching mechanism to store frequently accessed data based on zone ID, stability, and priority. The performance of QWLCPM is evaluated through simulations and compared with other forwarding and caching algorithms. QWLCPM’s efficacy stems from its holistic decision-making process, incorporating spatial and temporal elements for efficient cache management. Zone-based caching, showcased in different scenarios, enhances content delivery by utilizing stable nodes. QWLCPM’s proximity considerations significantly improve cache hits, reduce delay, and optimize hop count, especially in scenarios with sparse traffic. Additionally, its priority-based caching mechanism enhances hit ratios and content diversity, emphasizing QWLCPM’s substantial network-improvement potential in vehicular environments. These findings suggest that QWLCPM has the potential to greatly enhance QoS in NDVSNs and serve as a promising solution for future vehicular sensor networks. Future research could focus on refining the details of its implementation, scalability in larger networks, and conducting real-world trials to validate its performance under dynamic conditions.

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Roadside Unit Transmission Control for Energy Efficiency in Vehicle-to-Infrastructure Communication Network

Cited by 2 publications

References 0 publications

Modeling a LoRAWAN Network for Vehicle Wildlife Collision Avoidance System on Rural Roads

Modeling a LoRAWAN Network for Vehicle Wildlife Collision Avoidance System on Rural Roads

QWLCPM: A Method for QoS-Aware Forwarding and Caching Using Simple Weighted Linear Combination and Proximity for Named Data Vehicular Sensor Network

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