Optimizing MDS-coded cache-enable wireless network:a blockchain-based cooperative deep reinforcement learning approach

作     者：Zhang Zheng Yang Ruizhe Yu Fei Richard Zhang Yanhua Li Meng 张正;Yang Ruizhe;Yu Fei Richard;Zhang Yanhua;Li Meng

作者机构：Faculty of Information TechnologyBeijing University of TechnologyBeijing 100124P.R.China Department of Systems and Computer EngineeringCarleton UniversityOttawa K1S5B6Canada 

出 版 物：《High Technology Letters》 (高技术通讯（英文版）)

年 卷 期：2021年第27卷第2期

页      面：129-138页

核心收录：

学科分类：080904[工学-电磁场与微波技术] 0810[工学-信息与通信工程] 12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 080402[工学-测试计量技术及仪器] 0804[工学-仪器科学与技术] 081001[工学-通信与信息系统] 

基　　金：Supported by the National Natural Science Foundation of China(No.61571021,61901011) the Program of China Scholarship Council(No.201806540039) 

主　　题：caching technology blockchain deep reinforcement learning(DRL) 

摘      要：Mobile distributed caching(MDC)as an emerging technology has drawn attentions for its ability to shorten the distance between users and data in the wireless ***,the DC network state in the existing work is always assumed to be either static or real-time *** be more realistic,a periodically updated wireless network using maximum distance separable(MDS)-coded DC is studied,in each period of which the devices may arrive and *** the efficient optimization of the system with large scale,this work proposes a blockchain-based cooperative deep reinforcement learning(DRL)approach,which enhances the efficiency of learning by cooperating and guarantees the security in cooperation by the practical Byzantine fault tolerance(PBFT)-based blockchain *** results are presented,and it illustrates that the proposed scheme can dramatically reduce the total file download delay in DC network under the guarantee of security and efficiency.