Multi-chain and data-chains partitioning algorithm in intelligent manufacturing CPS

Li, Suisheng; Hong, Xia; Qiao, Jingwei

doi:10.1186/s13677-021-00227-9

Cited by 11 publications

(8 citation statements)

References 20 publications

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“…Payment channels [86], [87] Sidechains [41], [88] Cross-chain [89], [90], [91], [92], [93], [94], [69], [70] Off-chain [71], [95], [96], [97], [98], [99]…”

Section: Scalability Solutionsmentioning

confidence: 99%

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Scalability Solutions in Blockchain-Supported Manufacturing: A Survey

Rožman¹,

Corn²,

Škulj³

et al. 2022

sv-jme

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Researchers in the field of smart manufacturing have recognized the benefits of blockchain technology, which solves the trust problem in the open network without relying on any trusted third party. Blockchain technology enables interaction between otherwise competing manufacturing entities to satisfy increasing customer demands in a trustful way. However, existing blockchain networks are facing limitations, which are defined by the trade-off between scalability, decentralization, and security. The scalability of the blockchain network is defined as the ability of the network to support an increasing load of transactions and it is lower compared to the non-blockchain systems. In order to omit the effects of the limitations, scalability solutions are being presented. This research reviews the literature in the field of blockchain-supported manufacturing concerning scalability solutions. The selected literature has been reviewed and classified according to the type of scalability solution. For each type of scalability solution, the main features of the concepts and connection between blockchain technology and manufacturing system are highlighted and discussed. The main findings of the study are that Layer 1 scalability solutions are better represented in the literature and are predominating in the case of general smart manufacturing systems, whereas Layer 2 scalability solutions are better represented in the case of specific smart manufacturing systems. Based on insights obtained from the presented analysis, future directions and open issues regarding the scalability limitations and solutions in blockchain-supported manufacturing are presented.

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“…Payment channels [86], [87] Sidechains [41], [88] Cross-chain [89], [90], [91], [92], [93], [94], [69], [70] Off-chain [71], [95], [96], [97], [98], [99]…”

Section: Scalability Solutionsmentioning

confidence: 99%

“…A notary scheme is the selected cross-chain protocol also in the algorithm for the blockchainsupported system on multi-chain storage for cyber, physical, and social (CPS) under edge cloud computing [91]. Blockchain-supported CPS systems are generating a huge amount of similar data that occupies the storage of the devices in the system.…”

Section: Cross-chainmentioning

confidence: 99%

Scalability Solutions in Blockchain-Supported Manufacturing: A Survey

Rožman¹,

Corn²,

Škulj³

et al. 2022

sv-jme

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show abstract

“…A separate chain was built to record the usage of privacy budget in the multichain blockchain. The nodes of supply chain financial blockchain are divided into several groups according to relationship of communication tightness via community clustering partition algorithm 6 . According to the partition results, a multi‐chain blockchain was established.…”

Section: Privacy Budget Management Based On Multichain Structurementioning

confidence: 99%

“…Ethereum achieved multi-chain structure by slicing technology which was considered to be an effective solution for the scalability problem of blockchain 4 Hyperledger generated a private "subnet" for communication between two or more members by multichannel technology, and different members needed to complete identification and authorization before trading. 5 In the research of multichain partition, Li et al 6 proposed a community clustering partition algorithm in which the nodes of system were divided according to the relationship of communication tightness. In the research of blockchain privacy protection, Jia et al 7 proposed an incentive mechanism for blockchain location privacy protection in crowd aware networks, which was a hybrid incentive mechanism combining privacy protection and virtual credit.…”

Section: Introductionmentioning

confidence: 99%

Privacy budget management and noise reusing in multichain environment

Jiang

et al. 2021

Int J of Intelligent Sys

Self Cite

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To solve the problem of query restriction in supply‐chain financial blockchain system, this paper proposes a privacy budget management and noise reusing method in multichain blockchain environment based on Hyperledger multichannel technology and community clustering algorithm. A historical record book is established to manage the privacy budget according to historical query types, and a differential privacy protection algorithm based on noise reusing is used to generate and reusing noise. In the experiments, we tested the privacy budget loss, data utility and system performance based on the business data‐set from chemical supply chain. The experimental results show that the blockchain system with multichain structure based on community clustering algorithm reduces the system data storage space and decreases request processing time effectively. The privacy budget loss of the proposed method is about 1/3 of that of the pure Gaussian mechanism method. After 100 queries, the total amount of noise is about 8% less than that of pure Gaussian mechanism. Besides that, the noise reusing algorithm reduces the loss of the privacy budget and breaks through the query limitation caused by privacy budget wasting.

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“…A cloud-assisted and edge-decision-making manufacturing architecture with production edges was introduced by Tang et al [ 44 ]. Meanwhile, machine learning [ 45 ], the compound dual innovation capability model [ 46 ], the capability maturity model [ 47 ], the information model of a lithium ion battery intelligent manufacturing workshop [ 48 ], the neural network [ 49 ], the predictive maintenance method [ 50 ], and the multichain and data-chain partitioning algorithm [ 51 , 52 , 53 ] have also been studied to improve the intelligent methods in intelligent manufacturing.…”

Section: Introductionmentioning

confidence: 99%

Intelligent Manufacturing Technology in the Steel Industry of China: A Review

Zhou

et al. 2022

Sensors

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Intelligent manufacturing, defined as the integration of manufacturing with modern information technologies such as 5G, digitalization, networking, and intelligence, has grown in popularity as a means of boosting the productivity, intelligence, and flexibility of traditional manufacturing processes. The steel industry is a necessary support for modern life and economic development, and the Chinese steel industry’s capacity has expanded to roughly half of global production. However, the Chinese steel industry is now confronted with high labor costs, massive carbon emissions, a low level of intelligence, low production efficiency, and unstable quality control. Therefore, China’s steel industry has launched several large-scale intelligent manufacturing initiatives to improve production efficiency, product quality, manual labor intensity, and employee working conditions. Unfortunately, there is no comprehensive overview of intelligent manufacturing in China’s steel industry. We began this research by summarizing the construction goals and overall framework for intelligent manufacturing of the steel industry in China. Following that, we offered a brief review of intelligent manufacturing for China’s steel industry, as well as descriptions of two typical intelligent manufacturing models. Finally, some major technologies employed for intelligent production in China’s steel industry were introduced. This research not only helps to comprehend the development model, essential technologies, and construction techniques of intelligent manufacturing in China’s steel industry, but it also provides vital inspiration for the manufacturing industry’s digital and intelligence updates and quality improvement.

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Multi-chain and data-chains partitioning algorithm in intelligent manufacturing CPS

Cited by 11 publications

References 20 publications

Scalability Solutions in Blockchain-Supported Manufacturing: A Survey

Scalability Solutions in Blockchain-Supported Manufacturing: A Survey

Privacy budget management and noise reusing in multichain environment

Intelligent Manufacturing Technology in the Steel Industry of China: A Review

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