A Review on VANET Research: Perspective of Recent Emerging Technologies

Mahi, Md. Julkar Nayeen; Chaki, Sudipto; Ahmed, Shamim; Biswas, Milon; Kaiser, M. Shamim; Islam, Mohammad Shahidul; Sookhak, Mehdi; Barros, Alistair; Whaiduzzaman, Md

doi:10.1109/access.2022.3183605

Cited by 66 publications

(25 citation statements)

References 108 publications

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“…It is obvious from these studies that the performance of both standards is influenced by CW size, variation of traffic, and vehicle velocity. The performance for sm is crucial [20], [21] in VANETs which has been investigated in [12]- [14]. However, in [12], backoff freezing and velocity are not taken into account, and just the IEEE 802.11p standard is used.…”

Section: Related Workmentioning

confidence: 99%

Optimizing Vehicular Safety Message Communications by Adopting Transmission Probability With CW Size

et al. 2022

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Vehicular ad hoc networks (VANETs) will have noteworthy breakthroughs with the upcoming 5G and 6G technologies. In VANETs, the performance changes with traffic, contention window (CW) size, and vehicle velocity. Since the velocity and number of vehicles are not controllable, CW size will be optimized to maximize performance. In this paper, performance is optimized for highly important safety messages (sm) in VANETs by optimizing CW size with respect to number of vehicles and vehicle velocity. If any of these parameters (velocity and/or number of vehicles) changes, CW size will be dynamically adjusted to keep performance at optimum level. The comparison between IEEE 802.11 and IEEE 802.11p for sm in VANETs is presented where performance is maximized for both IEEE 802.11 and IEEE 802.11p. Markov chain based analytical model is developed and optimum expressions are derived. SUMO is used to build the microscopic mobility model. Monte Carlo simulation results are provided which verify analytical study and demonstrate that the performance is maximized regardless of parameters variation.

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Section: Related Workmentioning

confidence: 99%

Optimizing Vehicular Safety Message Communications by Adopting Transmission Probability With CW Size

et al. 2022

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“…A Mobile Ad Hoc Network (MANET) is a collection of wireless devices called nodes that move within an environment [1]. These nodes can communicate with each other without a particular infrastructure.…”

Section: Introductionmentioning

confidence: 99%

“…Also, MANET networks contain mobile nodes that change their positions over time. This makes it a challenging task when nodes exchange information [1], [2].…”

Section: Introductionmentioning

confidence: 99%

Vanet performance evaluatıon ın terms of nodes dıstrıbutıon, mobılıty models, and routıng protocols

Ismael¹,

Uçan²

2023

Technium

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Nowadays, Vehicle Ad Hoc Networks (VANETs) have become a new trend and one of the most attractive areas of research. It has a wide range of applications such as smart cities and the Internet of Things (IoT). The main issue of the VANET networks is the limitation in network resources such as power, and memory. Moreover, since VANET nodes are dynamic and move over time, the connectivity of the networks is also considered an important issue. This paper designs experiments that reflect a variety of scenarios in VANET networks. Many issues and factors in VANET networks have also been investigated in this paper. There are many factors that affect the whole performance of VANET networks (i.e., mobility models, routing protocols, and things distribution) in terms of network resources. Therefore, this paper aims at testing different mobility models such as the Human Mobility model, Cauchy Flight Mobility model, and Correlated Directions Mobility model, and investigate their impact on the consumption of network resources under a particular routing protocol such as Spray and Wait routing protocol, Probabilistic Flooding routing protocol, and Epidemic routing protocol. In addition, testing different distributions such as Uniform distribution, Gaussian (Normal) distribution, and Power-Law distribution). The resources we plan to investigate are energy sources and the amount of data exchanged. In the designed experiments, each simulation includes a combination of a mobility model, nodes distribution, and a routing protocol. The findings showed that each mobility model, routing protocol, or distribution is effective in a particular application. As a result, it was found that determining the application of the VANET network is a crucial step before performing a simulation or designing a network.

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“…Increase in the number of vehicles due to technological advancement, presence of On Board Unit (OBU) in the vehicle for the data communication [11], availability of vehicular standards like Wireless Access in Vehicular Environment (WAVE) [12], Dedicated Short Range Communications (DSRC) [13], physical. MAC layer service provision by IEEE 802.1 p [14], availability of 5G for faster data communication in vehicular network [15,16] helps to use VANET for a wide range of applications [17]. Based on the available communication network component, communication in VANET is broadly classified into four categories.…”

Section: Introductionmentioning

confidence: 99%

AI-assisted Emergency Healthcare using Vehicular Network and Support Vector Machine

Senapati

Khilar

Dash

et al. 2023

Wireless Pers Commun

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The COVID-19 pandemic has created an emergency across the globe. The number of corona positive and death cases is still rising worldwide. All countries’ governments are taking various steps to control the infection of COVID-19. One step to control the coronavirus’s spreading is to quarantine. But the number of active cases at the quarantine center is increasing daily. Also, the doctors, nurses, and paramedical staff providing service to the people at the quarantine center are getting infected. This demands the automatic and regular monitoring of people at the quarantine center. This paper proposed a novel and automated method for monitoring people at the quarantine center in two phases. These are the health data transmission phase and health data analysis phase. The health data transmission phase proposed a geographic-based routing that involves components like Network-in-box, Roadside-unit, and vehicles. An effective route is determined using route value to transmit data from the quarantine center to the observation center. The route value depends on the factors such as density, shortest path, delay, vehicular data carrying delay, and attenuation. The performance metrics considered for this phase are E2E delay, number of network gaps, and packet delivery ratio, and the proposed work performs better than the existing routing like geographic source routing, anchor-based street traffic aware routing, Peripheral node based GEographic DIstance Routing . The analysis of health data is done at the observation center. In the health data analysis phase, the health data is classified into multi-class using a support vector machine. There are four categories of health data: normal, low-risk, medium-risk, and high-risk. The parameters used to measure the performance of this phase are precision, recall, accuracy, and F-1 score. The overall testing accuracy is found to be 96.8%, demonstrating strong potential for our technique to be adopted in practice.

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A Review on VANET Research: Perspective of Recent Emerging Technologies

Cited by 66 publications

References 108 publications

Optimizing Vehicular Safety Message Communications by Adopting Transmission Probability With CW Size

Optimizing Vehicular Safety Message Communications by Adopting Transmission Probability With CW Size

Vanet performance evaluatıon ın terms of nodes dıstrıbutıon, mobılıty models, and routıng protocols

AI-assisted Emergency Healthcare using Vehicular Network and Support Vector Machine

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