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Title	Trustworthy Transaction Spreading Using Node Reliability Estimation In Iot Blockchain Networks
ID_Doc	59126
Authors	Kim J.; Kim J.-H.
Year	2022
Published	Applied Sciences (Switzerland), 12, 17
DOI	http://dx.doi.org/10.3390/app12178737
Abstract	Featured Application: Blockchain-powered IoT Applications, such as agricultural applications, logistics, and smart factory data management. Blockchain network architecture is a promising technology for constructing highly secure Internet of Things (IoT) networks. IoT networks typically comprise various sensors and actuators. Blockchain network technology can be applied to secure control robots in smart factories or reliable drone deliveries in smart cities. The wide spread of transactions and shared smart contracts across blockchain networks guarantees ultimate network security. A typical wired blockchain network maintains sufficient redundancy within a stable configuration. However, IoT blockchain networks exhibit unavoidable instability. The dynamic configuration changes caused by flexible node membership make it impossible to achieve the same level of redundancy as a stable network. A trustworthy transaction spreading method provides practical transaction sharing for dynamic IoT networks. We propose a Q-learning framework and a graph convergence network (GCN) to search for the proper spreading path of each transaction. The proposed Q-learning framework determines the next spreading hop using node features. The GCN determines the reliable area based on the Q-learning results. The discovered reliable area guides the proper spreading path of transactions to the destination node. In addition, the proposed trustworthy transaction spreading was implemented over an InterPlanetary File system (IPFS). The IPFS-powered experiments confirmed the practicability of the proposed transaction spreading mechanism. © 2022 by the authors.
Author Keywords	GCN; IoT blockchain; IPFS; Q-learning

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