Reliability and quality of service of an off-grid wind powered roadside unit in a motorway vehicular environment

Audu, George A.; Bhattacharya, Samya; Muhtar, Adnan; Qazi, Bilal R.; Elmirghani, Jaafar M. H.

doi:10.1016/j.vehcom.2017.07.001

Cited by 3 publications

(2 citation statements)

References 39 publications

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“…This evaluation encompasses a comprehensive assessment of both the availability and reliability metrics for all the models under consideration. Table 6 provides a detailed account of the parameter values assigned to various system components, with these values meticulously sourced from extant scholarly publications [40,[42][43][44]. The parameters detailed include those pertaining to the RSU group, the MTTF and MTTR for the Edge component, as well as the failure and repair durations associated with the network.…”

Section: Case Studymentioning

confidence: 99%

Urban Advanced Mobility Dependability: A Model-Based Quantification on Vehicular Ad Hoc Networks with Virtual Machine Migration

Silva,

Cardoso,

Brito

et al. 2023

Sensors

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In the rapidly evolving urban advanced mobility (UAM) sphere, Vehicular Ad Hoc Networks (VANETs) are crucial for robust communication and operational efficiency in future urban environments. This paper quantifies VANETs to improve their reliability and availability, essential for integrating UAM into urban infrastructures. It proposes a novel Stochastic Petri Nets (SPN) method for evaluating VANET-based Vehicle Communication and Control (VCC) architectures, crucial given the dynamic demands of UAM. The SPN model, incorporating virtual machine (VM) migration and Edge Computing, addresses VANET integration challenges with Edge Computing. It uses stochastic elements to mirror VANET scenarios, enhancing network robustness and dependability, vital for the operational integrity of UAM. Case studies using this model offer insights into system availability and reliability, guiding VANET optimizations for UAM. The paper also applies a Design of Experiments (DoE) approach for a sensitivity analysis of SPN components, identifying key parameters affecting system availability. This is critical for refining the model for UAM efficiency. This research is significant for monitoring UAM systems in future cities, presenting a cost-effective framework over traditional methods and advancing VANET reliability and availability in urban mobility contexts.

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Section: Case Studymentioning

confidence: 99%

Urban Advanced Mobility Dependability: A Model-Based Quantification on Vehicular Ad Hoc Networks with Virtual Machine Migration

Silva,

Cardoso,

Brito

et al. 2023

Sensors

View full text Add to dashboard Cite

show abstract

“…However, it is not fit for the renewable energy-powered RSUs. The off-grid windpowered RSUs are considered in [12]. Varied from conven-tional reliability analysis, the reliability in this paper is redefined in a highway environment.…”

Section: Related Workmentioning

confidence: 99%

Deep Learning‐Based Service Scheduling Mechanism for GreenRSUs in the IoVs

Wang

Seo

et al. 2021

Wireless Communications and Mobile Computing

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Green roadside units (RSUs), also called renewable energy-powered RSUs, are utilized recently rather than the traditional electric-powered RSUs with high power consumption and the large infrastructure deployment cost in the Internet of vehicles (IoVs). However, the power of the green RSUs is limited and unstable, which is affected by the battery size and charging environment. Therefore, a big challenge to deploy green RSUs in the IoVs is to schedule their service process properly, in order to extend the service efficiency of RSUs. In this paper, a deep learning-based communication scheduling mechanism is proposed regarding the service scheduling problem. In particular, a three-part scheduling algorithm consisting of RSU clustering, deep learning-based traffic prediction, and a vehicle access scheduling algorithm is presented to maximize the service number of vehicles and minimize the energy cost. An extensive simulation is done, and the simulation results indicate that our algorithm can serve more vehicles with less energy consumption compared with other scheduling mechanisms under different scenarios.

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Network slicing and efficient ONU migration for reliable communications in converged vehicular and fixed access network

Zhang

et al. 2018

Vehicular Communications

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Reliability and quality of service of an off-grid wind powered roadside unit in a motorway vehicular environment

Cited by 3 publications

References 39 publications

Urban Advanced Mobility Dependability: A Model-Based Quantification on Vehicular Ad Hoc Networks with Virtual Machine Migration

Urban Advanced Mobility Dependability: A Model-Based Quantification on Vehicular Ad Hoc Networks with Virtual Machine Migration

Deep Learning‐Based Service Scheduling Mechanism for GreenRSUs in the IoVs

Network slicing and efficient ONU migration for reliable communications in converged vehicular and fixed access network

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