A Blockchain-Based Traffic Conditions and Driving Behaviors Warning Scheme in the Internet of Vehicles

Bai, He; Wu, Cangshuai; Yang, Yuexiang; Xia, Geming; Jiang, Yuwei

doi:10.1109/icct46805.2019.8947312

Cited by 5 publications

(1 citation statement)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To guarantee the safety of data, several works [10,11] built blockchain systems for IoV. Bai et al [12] proposed a driving behavior warning scheme based on blockchain. The road information and driving data are regarded as transactions to ensure that the correct road condition is broadcast to other vehicle locations.…”

Section: Application Of Blockchain In the Vehicular Networkmentioning

confidence: 99%

A Trusted Edge Resource Allocation Framework for Internet of Vehicles

Zhong,

Xu,

Liao

et al. 2023

CMC

View full text Add to dashboard Cite

With the continuous progress of information technique, assisted driving technology has become an effective technique to avoid traffic accidents. Due to the complex road conditions and the threat of vehicle information being attacked and tampered with, it is difficult to ensure information security. This paper uses blockchain to ensure the safety of driving information and introduces mobile edge computing technology to monitor vehicle information and road condition information in real time, calculate the appropriate speed, and plan a reasonable driving route for the driver. To solve these problems, this paper proposes a trusted edge resource allocation framework for assisted driving service, which includes two stages: the blockchain generation stage (the first stage) and assisted driving service stage (the second stage). Furthermore, in the first stage, a delay-and-throughput-oriented block generation model for the mobile terminal is designed. In the second stage, a balanced offloading algorithm for assisted driving service based on edge collaboration is proposed to solve the problems of unbalanced load of cluster mobile edge computing (MEC) servers and low resource utilization of the system. And this paper optimizes the throughput of blockchain and delay of the transportation network through deep reinforcement learning (DRL) algorithm. Finally, compared with joint computation and communication resources' allocation (JCCR) and resource allocation method based on binary offloading (RAB), our proposed scheme can optimize the delay by 7.4% and 26.7%, and support various application services of the vehicular networks more effectively.

show abstract

Section: Application Of Blockchain In the Vehicular Networkmentioning

confidence: 99%