DRL-Based Adaptive Sharding for Blockchain-Based Federated Learning

doi:10.1109/TCOMM.2023.3288591

	DRL-Based Adaptive Sharding for Blockchain-Based Federated Learning
	Lin, Yijing 1; Gao, Zhipeng 1; Du, Hongyang 2; Kang, Jiawen 3; Niyato, Dusit 2; Wang, Qian4 ; Ruan, Jingqing 5; Wan, Shaohua 6
发表期刊	IEEE TRANSACTIONS ON COMMUNICATIONS
ISSN	0090-6778
	2023-10-01
卷号	71 期号:10 页码:5992-6004
通讯作者	Gao, Zhipeng(gaozhipeng@bupt.edu.cn)
摘要	Blockchain-based Federated Learning (FL) technology enables vehicles to make smart decisions, improving vehicular services and enhancing the driving experience through a secure and privacy-preserving manner in Intelligent Transportation Systems (ITS). Many existing works exploit two-layer blockchain-based FL frameworks consisting of a mainchain and subchains for data interactions among intelligent vehicles, which resolve the limited throughput issue of single blockchain-based vehicular networks. However, the existing two-layer frameworks still suffer from a) strong dependency on predetermined and fixed parameters of vehicular blockchains which limit blockchain throughput and reliability; and b) high communication costs incurred by interactions among intelligent vehicles between the mainchain and subchains. To address the above challenges, we first design an adaptive blockchain-enabled FL framework for ITS based on blockchain sharding to facilitate decentralized vehicular data flows among intelligent vehicles. A streamline-based shard transmission mechanism is proposed to ensure communication efficiency almost without compromising the FL accuracy. We further formulate the proposed framework and propose an adaptive sharding mechanism using Deep Reinforcement Learning to automate the selection of parameters of vehicular shards. Numerical results clearly show that the proposed framework and mechanisms achieve adaptive, communication-efficient, credible, and scalable data interactions among intelligent vehicles.
关键词	Blockchain sharding federated learning reputation deep reinforcement learning
DOI	10.1109/TCOMM.2023.3288591
关键词[WOS]	INTERNET ; OPTIMIZATION
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[62072049] ; National Natural Science Foundation of China[62101012] ; National Natural Science Foundation of China[62102099] ; BUPT Innovation and Entrepreneurship Support Program[2023-YC-A131] ; National Research Foundation, Singapore ; Infocomm Media Development Authority under its Future Communications Research & Development Programme ; DSO National Laboratories under the AI Singapore Programme[AISG2-RP-2020-019] ; Energy Research Test-Bed and Industry Partnership Funding Initiative ; Energy Grid (EG) 2.0 programme ; Campus for Research Excellence and Technological Enterprise (CREATE) programme ; MOE Tier 1[RG87/22]
项目资助者	National Natural Science Foundation of China ; BUPT Innovation and Entrepreneurship Support Program ; National Research Foundation, Singapore ; Infocomm Media Development Authority under its Future Communications Research & Development Programme ; DSO National Laboratories under the AI Singapore Programme ; Energy Research Test-Bed and Industry Partnership Funding Initiative ; Energy Grid (EG) 2.0 programme ; Campus for Research Excellence and Technological Enterprise (CREATE) programme ; MOE Tier 1
WOS研究方向	Engineering ; Telecommunications
WOS类目	Engineering, Electrical & Electronic ; Telecommunications
WOS记录号	WOS:001164689800002
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计	被引频次：10[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/57839
专题	复杂系统认知与决策实验室_听觉模型与认知计算
通讯作者	Gao, Zhipeng
作者单位	1.Beijing Univ Posts & Telecommun, State Key Lab Networking & Switching Technol, Beijing 100876, Peoples R China 2.Nanyang Technol Univ, Sch Comp Sci & Engn, Singapore 639798, Singapore 3.Guangdong Univ Technol, Sch Automat, Guangzhou 510006, Peoples R China 4.Beijing Univ Technol, Coll Comp Sci, Beijing 100124, Peoples R China 5.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China 6.Univ Elect Sci & Technol China, Shenzhen Inst Adv Study, Shenzhen 518110, Peoples R China
推荐引用方式 GB/T 7714	Lin, Yijing,Gao, Zhipeng,Du, Hongyang,et al. DRL-Based Adaptive Sharding for Blockchain-Based Federated Learning[J]. IEEE TRANSACTIONS ON COMMUNICATIONS,2023,71(10):5992-6004.
APA	Lin, Yijing.,Gao, Zhipeng.,Du, Hongyang.,Kang, Jiawen.,Niyato, Dusit.,...&Wan, Shaohua.(2023).DRL-Based Adaptive Sharding for Blockchain-Based Federated Learning.IEEE TRANSACTIONS ON COMMUNICATIONS,71(10),5992-6004.
MLA	Lin, Yijing,et al."DRL-Based Adaptive Sharding for Blockchain-Based Federated Learning".IEEE TRANSACTIONS ON COMMUNICATIONS 71.10(2023):5992-6004.