Reference : IoV-based Deployment and Scheduling of Charging Infrastructure in Intelligent Transpo...
Scientific journals : Article
Engineering, computing & technology : Electrical & electronics engineering
Security, Reliability and Trust
IoV-based Deployment and Scheduling of Charging Infrastructure in Intelligent Transportation Systems
Ejaz, Waleed []
Naeem, Mohammed []
Sharma, Shree Krishna mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom >]
Khattak, Asad K. []
Ramzan, M. R. []
Ali, Amjad []
Anpalagan, Alagan []
IEEE Sensors Journal
Institute of Electrical and Electronics Engineers
Yes (verified by ORBilu)
New York
[en] IoT ; IoV ; Electric Vehicles ; Charging Infrastructure ; Scheduling Optimization
[en] Internet of vehicles (IoV) is an emerging paradigm
to exchange and analyze information collected from sensors
using wireless technologies between vehicles and people, vehicles
and infrastructure, and vehicles-to-vehicles. With the recent
increase in the number of electric vehicles (EVs), the seamless
integration of IoV in EVs and charging infrastructure can offer
environmentally sustainable and budget-friendly transportation.
In this paper, we propose an IoV-based framework that consists of
deployment and scheduling of a mobile charging infrastructure.
For the deployment, we formulate an optimization problem to
minimize the total cost of mobile charging infrastructure placement
while considering constraints on the number of EVs that
can be charged simultaneously. The formulated problem is mixedinteger
programming and solved by using the branch and bound
algorithm. We then propose an IoV-based scheduling scheme for
EVs charging to minimize travel distance and charging costs
while satisfying the constraints of charging time requirement of
EVs and resources of a charging station.We consider passive road
sensors and traffic sensors in the proposed IoV-based scheduling
scheme to enable EV users for finding a charging station that can
fulfill their requirements, as well as to enable service providers to
know about the demand in the area. Simulation results illustrate
the significant impact of the optimal deployment of charging
infrastructure and scheduling optimization on the efficiency of
EVs charging.
Researchers ; Professionals ; Students ; General public ; Others

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