作者
Yueyue Dai, Du Xu, Ke Zhang, Sabita Maharjan, Yan Zhang
发表日期
2020/2/13
期刊
IEEE Transactions on Vehicular Technology
卷号
69
期号
4
页码范围
4312-4324
出版商
IEEE
简介
Vehicular Edge Computing (VEC) is a promising paradigm to enable huge amount of data and multimedia content to be cached in proximity to vehicles. However, high mobility of vehicles and dynamic wireless channel condition make it challenge to design an optimal content caching policy. Further, with much sensitive personal information, vehicles may be not willing to caching their contents to an untrusted caching provider. Deep Reinforcement Learning (DRL) is an emerging technique to solve the problem with high-dimensional and time-varying features. Permission blockchain is able to establish a secure and decentralized peer-to-peer transaction environment. In this paper, we integrate DRL and permissioned blockchain into vehicular networks for intelligent and secure content caching. We first propose a blockchain empowered distributed content caching framework where vehicles perform content caching …
引用总数
学术搜索中的文章