An IoT and Edge Computing Based Framework for Charge Scheduling and EV Selection in V2G Systems

Chamola, Vinay; Sancheti, Ashutosh; Chakravarty, Sombuddha; Kumar, Neeraj; Guizani, Mohsen

doi:10.1109/tvt.2020.3013198

Cited by 43 publications

(13 citation statements)

References 46 publications

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“…The EV charging strategy and route planning is an inevitable problem in recent years, the traveling time and cost [5,6,11,13,21], waiting time in FCSs [7,8,10], user satisfaction [4,22,12,14] are considered. Mostly, the above factors are analyzed jointly.…”

Section: Related Workmentioning

confidence: 99%

“…Due to low driving cost and carbon emission, EVs become one of the fastest development in intelligence transportation systems (ITSs) [1,2]. Combined with the 5G communication technology, EVs transform to the critical part of the vehicular edge computing networks (VECNs), the driving experience of EVs is improved significantly [3,4]. The supporting environment of EVs is also gradually improved.…”

Section: Introductionmentioning

confidence: 99%

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Smart and Efficient EV Charging Navigation Scheme in Vehicular Edge Computing Networks

Li¹,

Chen²,

Liu³

et al. 2023

Preprint

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With the increasing number of electric fast charging stations (FCSs) deployed along roadsides of both urban roads and highways, the long-distance travel of electric vehicles (EVs) becomes possible. The EV charging navigation scheme is significant for the quality of user experience. However, the variable conditions of both power grid and traffic networks make it a serious challenge. In this paper, we propose an efficient EV charging navigation scheme while considering both the electric and computation resource sharing. With the support of vehicular edge computing networks in intelligent transportation systems (ITSs), EVs perform both the flexible power load and edge computing nodes. When the traffic network in the established route starts to become congested, EVs can select to enter the nearest FCS. In addition to being supplemented by electric resources, EVs also benefit by sharing their own computing resource with FCSs. We formulate the EV charging navigation as a mixed integer programming problem, the EV moving route planning, FCS selection, and staying time in FCSs are optimized, to balance the relationships among the traveling time, traveling cost and reward. To address the influence caused by the randomness of traffic conditions and charging prices, a two-stage charging navigation algorithm combined with A* algorithm and deep reinforcement learning (DRL) is proposed, with a novel designed reward function. Eventually, numerous experimental results show the effectiveness of the proposed schemes.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Smart and Efficient EV Charging Navigation Scheme in Vehicular Edge Computing Networks

Li¹,

Chen²,

Liu³

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…An intelligent framework based on IoT and edge computing has been proposed for the efficient operation of V2G. This framework can effectively provide active power regulation [83] , load matching, current harmonic filtering [84] , etc. It can also manage decentralized energy sources, increasing the grid's stability and reliability as well as its power efficiency [85] .…”

Section: Iot In Energy and Transportation Systemsmentioning

confidence: 99%

Shaping future low-carbon energy and transportation systems: Digital technologies and applications

Song

Wang

et al. 2022

iEnergy

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Digitalization and decarbonization are projected to be two major trends in the coming decades. As the already widespread process of digitalization continues to progress, especially in energy and transportation systems, massive data will be produced, and how these data could support and promote decarbonization has become a pressing concern. This paper presents a comprehensive review of digital technologies and their potential applications in low-carbon energy and transportation systems from the perspectives of infrastructure, common mechanisms and algorithms, and system-level impacts, as well as the application of digital technologies to coupled energy and transportation systems with electric vehicles. This paper also identifies corresponding challenges and future research directions, such as in the field of blockchain, digital twin, vehicle-to-grid, low-carbon computing, and data security and privacy, especially in the context of integrated energy and transportation systems.

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“…Conceptually, it is just more efficient resource allocation. Many studies have focused on developing intelligent parking mechanisms [85], [86], for example Zhang et al proposed a blockchain-based smart parking framework that links customers to available parking lots [58].…”

Section: B Transportationmentioning

confidence: 99%

A Comprehensive Survey on the Applications of Blockchain for Securing Vehicular Networks

Alladi¹,

Chamola²,

Sahu³

et al. 2022

Preprint

Self Cite

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Vehicular networks promise features such as traffic management, route scheduling, data exchange, entertainment, and much more. With any large-scale technological integration comes the challenge of providing security. Blockchain technology has been a popular choice of many studies for making the vehicular network more secure. Its characteristics meet some of the essential security requirements such as decentralization, transparency, tamper-proof nature, and public audit. This study catalogues some of the notable efforts in this direction over the last few years. We analyze around 75 blockchain-based security schemes for vehicular networks from an application, security, and blockchain perspective. The application perspective focuses on various applications which use secure blockchainbased vehicular networks such as transportation, parking, data sharing/ trading, and resource sharing. The security perspective focuses on security requirements and attacks. The blockchain perspective focuses on blockchain platforms, blockchain types, and consensus mechanisms used in blockchain implementation. We also compile the popular simulation tools used for simulating blockchain and for simulating vehicular networks. Additionally, to give the readers a broader perspective of the research area, we discuss the role of various state-of-the-art emerging technologies in blockchain-based vehicular networks. Lastly, we summarize the survey by listing out some common challenges and the future research directions in this field.

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An IoT and Edge Computing Based Framework for Charge Scheduling and EV Selection in V2G Systems

Cited by 43 publications

References 46 publications

Smart and Efficient EV Charging Navigation Scheme in Vehicular Edge Computing Networks

Smart and Efficient EV Charging Navigation Scheme in Vehicular Edge Computing Networks

Shaping future low-carbon energy and transportation systems: Digital technologies and applications

A Comprehensive Survey on the Applications of Blockchain for Securing Vehicular Networks

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