A roadside unit deployment framework for enhancing transportation services in Maghrebian cities

Chaabene, Seif Ben; Yeferny, Taoufik; Yahia, Sadok Ben

doi:10.1002/cpe.5611

Cited by 7 publications

(3 citation statements)

References 16 publications

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“…An RSU comprises various short‐range receivers (Charitos & Kalivas, 2017; Mekki et al, 2021) to provide consistent communication amongst vehicles, which comes under device transmission range called vehicle‐to‐infrastructure (V2I) communications. In some cases, the RSUs act as a relay amongst the vehicles (Ahmed & Gharavi, 2018; Ben Chaabene et al, 2021). Dedicated short‐range communications (DSRC) technology (Chen et al, 2017; Hui et al, 2018a), remains used to make sustainable connections between vehicles since the RSUs are limited with short communication range.…”

Section: Introductionmentioning

confidence: 99%

Deep learning‐influenced joint vehicle‐to‐infrastructure and vehicle‐to‐vehicle communication approach for internet of vehicles

Mekala

Patan²,

Kallam³

et al. 2021

Expert Systems

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The internet of vehicle (IoV) orchestration is an emerging technology in heterogeneous vehicles to contrivance diverse intelligent transportation applications. The roadside unit (RSU) plays a vital role during service provisioning. Vehicle-to-vehicle and vehicle-to-infrastructure communications have consistently accomplished the services in a vehicular network. However, persisting the increased vehicles' quality of experience and network vendors' utilities and which RSUs have to select for effective, reliable service are critical open research challenges to consolidate RSU services to enhance network service utility rate. In this article, we design a deep learninginspired RSU Service Consolidation Approach based on two-models to enhance the service reliability by formulating the RSU coverage issue with the RSU Migration model and content delivery issue with Linear Programming-based Multicast model. Adaptive Packet-Error measurement system to optimize service reliability rate at the edge of cooperative vehicular network based on content correlation. The performance and efficiency are examined based on MATLAB. The simulation outcomeshows RSC approach has low execution cost by 39%, service reliability rate by 71% than the state-of-art approaches.

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Section: Introductionmentioning

confidence: 99%

Deep learning‐influenced joint vehicle‐to‐infrastructure and vehicle‐to‐vehicle communication approach for internet of vehicles

Mekala

Patan²,

Kallam³

et al. 2021

Expert Systems

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“…The first paper, entitled “A RoadSide Unit Deployment Framework for Enhancing Transportation Services in Maghrebian Cities” by Chaabene et al 1 . addresses the problem of roadside units (RSUs) deployment in Maghribian cities.…”

Section: Introductionmentioning

confidence: 99%

Towards understanding and harnessing the potential of Africa in digitalization

Benkrid

Badir

Lô

et al. 2020

Concurrency and Computation

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Towards understanding and harnessing the potential of Africa in digitalization 1 BACKGROUND Nowadays, the digital transformation is an intensive subject that refers to all the changes related to a process with the integration of advanced digital technologies such as cloud computing, Internet of Things, three-dimensional printing, artificial intelligence, and transportation in all aspects of human society. Digitalization affects any firm, any sector, any type of job, any function in organizations/institutions. Then it has become ubiquitous in multiple domains such as oil and gas, disease management, finance, banking, transportation, education, healthcare, agriculture, energy, environment, gastronomy, government services, and so forth. Africa is the world's second-largest and second-most-populous continent. Despite a wide range of natural resources, the continent suffers from many problems such as poverty, diseases, illiteracy, weak infrastructure, political instability, and conflicts. The continent features a relatively young population, as well as a diaspora of expatriate African researchers all willing to contribute to its development. Digital communication has spread very fast with improved access to the Internet. All these must enable an African shift to a successful digitalization transformation story with the promotion of technological advancements. The promotion of high education and research in Africa is one of the important keys for achieving digital transformation. This special issue has been launched by five researchers: four from African countries: Algeria, Morocco, Senegal, and Tunisia, and one from the African diaspora, working in France. This issue is dedicated to African young researchers contributing to digitalization efforts. An open call for papers has been organized, where it attracted 25 papers covering topics related to digitalization transformation, more particularly big data analytics, data integration, data mining, social media data exploitation, decision support systems, cloud computing, smart applications, Internet of Things, data security and risk, web services, quality of data transmission, recommendation, and combinatorial optimization methods. All submissions were peer-reviewed by at least two reviewers from our international program committee consisting of academia and industrials from 12 different countries and working on the various topics of our special issues. After two rounds of reviews, we finally accepted 11 papers, making an acceptance rate of 44%. One of the interesting characteristics of our accepted papers is that some of them integrate real case studies involving important domains in Africa such as Algerian mobile telecommunication and transportation services in the Maghreb countries. We

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“…Coverage ratio: This important metric is calculated by dividing the number of valid coverage sub-roads by the total number of sub-roads in the road network; it indicates the ratio of road segments coverage in the network [56]. Subtracting duplicated sub-roads from all sub-roads yields the number of legitimate coverage sub-roads.…”

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confidence: 99%

Roadside Unit Deployment in Internet of Vehicles Systems: A Survey

Guerna

Bitam

Calafate

2022

Sensors

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In recent years, the network technology known as Internet of Vehicles (IoV) has been developed to improve road safety and vehicle security, with the goal of servicing the digital demands of car drivers and passengers. However, the highly dynamical network topology that characterizes these networks, and which often leads to discontinuous transmissions, is one of the most significant challenges of IoV. To address this issue, IoV infrastructure-based components known as roadside units (RSU) are designed to play a critical role by providing continuous transmission coverage and permanent connectivity. However, the main challenges that arise when deploying RSUs are balancing IoVs’ performances and total cost so that optimal vehicle service coverage is provided with respect to some target Quality of Service (QoS) such as: service coverage, throughput, low latency, or energy consumption. This paper provides an in-depth survey of RSU deployment in IoV networks, discussing recent research trends in this field, and summarizing of a number of previous papers on the subject. Furthermore, we highlight that two classes of RSU deployment can be found in the literature—static and dynamic—the latter being based on vehicle mobility. A comparison between the existing RSU deployment schemes proposed in existing literature, as well as the various networking metrics, are presented and discussed. Our comparative study confirms that the performance of the different RSU placement solutions heavily depends on several factors such as road shape, particularity of road segments (like accident-prone ones), wireless access methods, mobility model, and vehicles’ distribution over time and space. Besides that, we review the most important RSU placement approaches, highlighting their strengths and limitations. Finally, this survey concludes by presenting some future research directions in this domain.

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A roadside unit deployment framework for enhancing transportation services in Maghrebian cities

Cited by 7 publications

References 16 publications

Deep learning‐influenced joint vehicle‐to‐infrastructure and vehicle‐to‐vehicle communication approach for internet of vehicles

Deep learning‐influenced joint vehicle‐to‐infrastructure and vehicle‐to‐vehicle communication approach for internet of vehicles

Towards understanding and harnessing the potential of Africa in digitalization

Roadside Unit Deployment in Internet of Vehicles Systems: A Survey

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