Efficient Consensus and Elastic Resource Allocation Empowered Blockchain for Vehicular Networks

Lin, Yijing; Kang, Jiawen; Niyato, Dusit; Gao, Zhipeng; Wang, Qian

doi:10.1109/tvt.2022.3226495

Cited by 4 publications

(1 citation statement)

References 13 publications

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“…Blockchain has been integrated with VEC to ensure the security and privacy of V2X applications [14]- [16]. By incorporating blockchain technology into VEC to support V2X services, it is possible to create a highly effective and secure data-sharing infrastructure among VEC servers.…”

Section: Introductionmentioning

confidence: 99%

A Blockchain-Enabled Vehicular Edge Computing Framework for Secure Performance-oriented V2X Service Delivery

Fardad,

Muntean,

Tal

2024

IEEE Trans. Veh. Technol.

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Vehicular Edge Computing (VEC) has emerged as a promising paradigm to enable low-latency Vehicle-to-Everything (V2X) services by bringing computing resources closer to vehicles. However, the high dynamicity of vehicular networks poses significant challenges in designing an optimal policy for delivering V2X services while ensuring security and timely service delivery. To address these challenges, this paper proposes a Blockchain-Enabled Vehicular Edge Computing (BEVEC) framework that employs a dual-layer verification process empowered with a permissioned blockchain to ensure data accuracy and integrity. A novel system utility function is designed to measure the performance of the BEVEC, which also serves as the basis for a consensus mechanism of the permissioned blockchain. To optimize this utility, a Deep Reinforcement Learning (DRL) algorithm is proposed to enable timely service delivery in BEVEC. Simulation-based results demonstrate the effectiveness of the proposed algorithm when compared to existing approaches. On average, it obtained an 18% reduction in latency, a 38% improvement in successful service delivery, and a 65% decrease in energy consumption.

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Section: Introductionmentioning

confidence: 99%

A Blockchain-Enabled Vehicular Edge Computing Framework for Secure Performance-oriented V2X Service Delivery

Fardad,

Muntean,

Tal

2024

IEEE Trans. Veh. Technol.

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Task offloading and resource allocation for blockchain‐enabled mobile edge computing

Fang,

Lin,

Liu

et al. 2023

IET Communications

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Mobile edge computing (MEC) has risen as an effective approach to support ubiquitous and prosperous mobile applications. Due to the strict delay requirements and the increasingly complex application environments, the computation efficiency and security have become the bottleneck that restricts the MEC system. Here, a blockchain‐enabled task offloading scheme is proposed, where the sensitive computation tasks of user terminals (UTs) can be offloaded to a blockchain‐assisted base station (BS). The MEC‐assisted BS helps UTs compute tasks while the blockchain consensus protocol ensures the security of the task offloading and computing process. To manage the allocation of computing resources between task offloading and blockchain consensus, the task offloading and resource allocation are formulated as a joint optimization problem. The aim of the problem is to minimize the energy consumption of UTs while guaranteeing the delay requirement. By transforming the original problem into a Markov decision process, a collective reinforcement learning algorithm is proposed to solve the problem in an online fashion. In the simulations, the convergence and the performance of the proposed scheme are evaluated. The simulation results show the effectiveness of the scheme.

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Unleashing the Power of Edge-Cloud Generative AI in Mobile Networks: A Survey of AIGC Services

Xu,

Du,

Niyato

et al. 2024

IEEE Commun. Surv. Tutorials

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Efficient Consensus and Elastic Resource Allocation Empowered Blockchain for Vehicular Networks

Cited by 4 publications

References 13 publications

A Blockchain-Enabled Vehicular Edge Computing Framework for Secure Performance-oriented V2X Service Delivery

A Blockchain-Enabled Vehicular Edge Computing Framework for Secure Performance-oriented V2X Service Delivery

Task offloading and resource allocation for blockchain‐enabled mobile edge computing

Unleashing the Power of Edge-Cloud Generative AI in Mobile Networks: A Survey of AIGC Services

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