Consensus Mechanism for Blockchain-Enabled Vehicle-to-Vehicle Energy Trading in the Internet of Electric Vehicles

Abishu, Hayla Nahom; Seid, Abegaz Mohammed; Yacob, Yasin Habtamu; Ayall, Tewodros Alemu; Liu, Guisong

doi:10.1109/tvt.2021.3129828

Cited by 80 publications

(24 citation statements)

References 53 publications

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“…For example, EOS [7] uses a DPoS method that selects a specific number of validators to conduct the blockchain consensus process. In addition, in [18], Abishu et al proposed a PBFT-based proof of reputation consensus model for blockchain-based energy trading system in electric vehicles. The consensus model selects a set number of validators using the reputation of vehicles based on evaluations of each other.…”

Section: B Consensus Algorithms On Blockchainmentioning

confidence: 99%

Secure Trust-Based Delegated Consensus for Blockchain Frameworks Using Deep Reinforcement Learning

et al. 2022

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IoT (IoT) networks generate massive amounts of data while supporting various applications, where the security and protection of IoT data are very important. In particular, blockchain technology supporting IoT networks is considered as the most secure, expandable, and scalable database storage solution. However, existing blockchain systems have scalability problems due to low throughput and high resource consumption, and security problems due to malicious attacks. Several studies have proposed blockchain technologies that can improve the scalability or the security level, but there have been few studies that improve both at the same time. In addition, most existing studies do not consider malicious attack scenarios in the consensus process, which deteriorates the blockchain security level. In order to solve the scalability and security problems simultaneously, this paper proposes a Dueling Double Deep-Q-network with Prioritized experience replay (D3P) based secure trust-based delegated consensus blockchain (TDCB-D3P) scheme that optimizes the blockchain performance by applying deep reinforcement learning (DRL) technology. The TDCB-D3P scheme uses a trust system with a delegated consensus algorithm to ensure the security level and reduce computing costs. In addition, DRL is used to compute the optimum blockchain parameters under the dynamic network state and maximize the transactions per second (TPS) performance and security level. The simulation results show that the TDCB-D3P scheme can provide a superior TPS and resource consumption performance. Furthermore, in blockchain networks with malicious nodes, the simulation results show that the proposed scheme significantly improves the security level when compared to existing blockchain schemes by effectively reducing the influence of malicious nodes.INDEX TERMS Blockchain, consensus algorithm, deep reinforcement learning (DRL), internet of things (IoT), trust.

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Section: B Consensus Algorithms On Blockchainmentioning

confidence: 99%

Secure Trust-Based Delegated Consensus for Blockchain Frameworks Using Deep Reinforcement Learning

et al. 2022

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“…To protect customers' privacy and reduce the power cost, a cloud-based scheduling method for EV charge and discharge management was proposed in [12]. A blockchain-enabled energy trading with the Stackelberg game model between V2V was studied in [13] to perform the optimization for the roles of the system operator, power buyers, and validator nodes. Demand response has been used as a method to shift the peak load.…”

Section: Related Workmentioning

confidence: 99%

“…The service rate of the edge and remote cloud servers are listed in Table 2. Since there is no traffic at the parking lots at off-peak hours [1][2][3][4][5][11][12][13][20][21][22][23][24], the number of remote cloud servers is zero. At peak hours 8, 9, and 16, more remote cloud servers are allocated to satisfy the average waiting time threshold.…”

Section: Performance Evaluation Of Cloud-based Ev Charging In Iovmentioning

confidence: 99%

Smart Electric Vehicle Charging in the Era of Internet of Vehicles, Emerging Trends, and Open Issues

et al. 2022

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The Internet of Vehicles (IoV), where people, fleets of electric vehicles (EVs), utility, power grids, distributed renewable energy, and communications and computing infrastructures are connected, has emerged as the next big leap in smart grids and city sectors for a sustainable society. Meanwhile, decentralized and complex grid edge faces many challenges for planning, operation, and management of power systems. Therefore, providing a reliable communications infrastructure is vital. The fourth industrial revolution, that is, a cyber-physical system in conjunction with the Internet of Things (IoT) and coexistence of edge (fog) and cloud computing brings new ways of dealing with such challenges and helps maximize the benefits of power grids. From this perspective, as a use case of IoV, we present a cloud-based EV charging framework to tackle issues of high demand in charging stations during peak hours. A price incentive scheme and another scheme, electricity supply expansion, are presented and compared with the baseline. The results demonstrate that the proposed hierarchical models improve the system performance and the quality of service (QoS) for EV customers. The proposed methods can efficiently assist system operators in managing the system design and grid stability. Further, to shed light on emerging technologies for smart and connected EVs, we elaborate on seven major trends: decentralized energy trading based on blockchain and distributed ledger technology, behavioral science and behavioral economics, artificial and computational intelligence and its applications, digital twins of IoV, software-defined IoVs, and intelligent EV charging with information-centric networking, and parking lot microgrids and EV-based virtual storage. We have also discussed some of the potential research issues in IoV to further study IoV. The integration of communications, modern power system management, EV control management, and computing technologies for IoV are crucial for grid stability and large-scale EV charging networks.

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“…The Ref. (Abishu et al, 2022) proposed a new consensus mechanism that takes advantage of practical PBFT and proof of reputation (PoR) and employs an incentive mechanism based on the Stackelberg game model to optimize the utility of the seller, buyer, and verifier nodes. The Ref.…”

Section: Power Grid Operation Rulesmentioning

confidence: 99%

A review of energy internet research considering interactive energy: The blockchain perspective

et al. 2022

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With the proposal of carbon peak and neutrality goals in China, new technologies such as multi-energy synergy technology, cyber physical systems, and multi-market integration technology have ushered in unprecedented opportunities and challenges. Energy Internet (EI) technology considering interactive energy has come into being. Interactive energy is a mechanism to achieve system balance by integrating economic means and power grid control technology, using “value” as a coordination method. It can promote the development and utilization of distributed renewable energy in the energy internet technology, so as to promote the clean, low-carbon, and intelligent development of energy. Blockchain can provide effective support for the development and application of EI because of its decentralized, open, autonomous, and information-immutable characteristics. In order to better cope with the challenges existing in EI, this article designs an analysis framework for EI from the blockchain perspective, which contains five dimensions, including engineering dimension, technical dimension, economic dimension, environmental dimension, and social dimension. It further refines the five dimensions aiming to comprehensively summarize the research status of the EI, which can promote its application in the development of all industries in society.

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Consensus Mechanism for Blockchain-Enabled Vehicle-to-Vehicle Energy Trading in the Internet of Electric Vehicles

Cited by 80 publications

References 53 publications

Secure Trust-Based Delegated Consensus for Blockchain Frameworks Using Deep Reinforcement Learning

Secure Trust-Based Delegated Consensus for Blockchain Frameworks Using Deep Reinforcement Learning

Smart Electric Vehicle Charging in the Era of Internet of Vehicles, Emerging Trends, and Open Issues

A review of energy internet research considering interactive energy: The blockchain perspective

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