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作者:

Yang, Zhaoxin (Yang, Zhaoxin.) | Yang, Ruizhe (Yang, Ruizhe.) | Yu, F. Richard (Yu, F. Richard.) | Li, Meng (Li, Meng.) | Zhang, Yanhua (Zhang, Yanhua.) | Teng, Yinglei (Teng, Yinglei.)

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EI Scopus SCIE

摘要:

Immutability, decentralization, and linear promoted scalability make the sharded blockchain a promising solution, which can effectively address the trust issue in the large-scale Internet of Things (IoT). However, currently, the throughput of sharded blockchains is still limited when it comes to high proportion of cross-shard transactions (CSTs). On the other hand, the assemblage characteristic of the collaborative computing in IoT has not been received attention. Therefore, in this article, we present a clustering-based sharded blockchain strategy for collaborative computing in the IoT, where the sharding of the blockchain system is implemented in two steps: K-means-clustering-based user grouping and the assignment of consensus nodes. In this framework, how to reasonably group the IoT users while simultaneously guaranteeing the system performance is the key point. Specifically, we describe the data transactions among IoT devices by data transaction flow graph (DTFG) based on a dynamic stochastic block model. Then, formed as a Markov decision process (MDP), the optimization of the cluster number (shard number) and the adjustment of consensus parameters are jointly trained by deep reinforcement learning (DRL). Simulation results show that the proposed scheme improves the scalability of the sharded blockchain in the IoT application.

关键词:

K-means clustering dynamic graph analysis deep reinforcement learning (DRL) Collaborative computing Internet of Things (IoT) sharded blockchain

作者机构:

  • [ 1 ] [Yang, Zhaoxin]Beijing Univ Technol, Fac Informat Technol, Beijing 100124, Peoples R China
  • [ 2 ] [Yang, Ruizhe]Beijing Univ Technol, Fac Informat Technol, Beijing 100124, Peoples R China
  • [ 3 ] [Li, Meng]Beijing Univ Technol, Fac Informat Technol, Beijing 100124, Peoples R China
  • [ 4 ] [Zhang, Yanhua]Beijing Univ Technol, Fac Informat Technol, Beijing 100124, Peoples R China
  • [ 5 ] [Teng, Yinglei]Beijing Univ Technol, Fac Informat Technol, Beijing 100124, Peoples R China
  • [ 6 ] [Yu, F. Richard]Carleton Univ, Dept Syst & Comp Engn, Ottawa, ON K1S 5B6, Canada
  • [ 7 ] [Teng, Yinglei]Beijing Univ Posts & Telecommun, Sch Elect Engn, Beijing Key Lab Space Ground Interconnect & Conve, Beijing 100876, Peoples R China

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来源 :

IEEE INTERNET OF THINGS JOURNAL

ISSN: 2327-4662

年份: 2022

期: 17

卷: 9

页码: 16494-16509

1 0 . 6

JCR@2022

1 0 . 6 0 0

JCR@2022

JCR分区:1

中科院分区:1

被引次数:

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SCOPUS被引频次: 62

ESI高被引论文在榜: 0 展开所有

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