Research On Blockchain-based Personalized Customization And Data Sharing In Industrial Internet Of Things

The industrial Internet of Things(IIoT),as a supporting technology for smart manufacturing,enables intelligent decision through the processing and analysis of data shared by data sharing systems.Through the IIoT technology,smart manufacturing realizes the optimization of resource allocation and manufacturing process,and finally promotes the development of the new manufacturing mode represented by personalized customization.Focusing on the existing IIoT architecture,how to achieve a clear division of power and responsibility among multiple manufacturers,and how to efficiently utilize distributed manufacturing resources among heterogeneous systems,are the keys to achieve personalized customization.Meanwhile,data sharing drives the IIoT towards networking,digitalization and intelligence,which helps manufacturing enterprises to reduce costs and improve efficiency,thus enhancing their core competitiveness.However,the centralized data sharing system still suffers from poor scalability,single points of failure,data security,etc.Through the chain structure of block,encryption algorithm,consensus mechanism and smart contract,the blockchain technology establishes a distributed and "trustless" environment.It not only avoids single points of failure,but also enhances the scalability.Moreover,the immutability and auditability of the on-chain data are also guaranteed,achieving a clear division of power and responsibility.Thus,it becomes a potential solution in IIoT scenarios.In this paper,the blockchain technology is adopted to optimize the personalized customization and data sharing.The specific content includes the following two aspects:(1)Focusing on the contradiction between the transaction processing efficiency and manufacturing efficiency faced by the personalized customization,this paper proposes a blockchain-based smart manufacturing system that divides the complex manufacturing process into tasks for management.A joint optimization mechanism of block size,task scheduling and supply-demand configuration is designed,which balances the product timeliness and throughput while satisfying the Quality of Service(QoS).In order to motivate customers to participate in the market,this paper models the customers'net profit and proposes a bipartite matching based online DQN(Deep Q Network)algorithm.Simulation results show that the proposed joint optimization mechanism is well adapted to the dynamic market environment.(2)Aiming at the data quality of data sharing,this paper first proposes an appropriate data quality evaluation mechanism.According to the predicted value of data quality and the reputation of nodes,a system payment strategy is modeled to encourage nodes upload high-quality data spontaneously.In addition,the data collection strategy for optimizing the economic benefits of nodes is also designed.In this paper,the solution of the payment strategy parameter of the system and the data collection frequency of nodes is modeled as a Stackelberg game,which is solved by Particle Swarm Optimization(PSO)to maximize the system utility and the node utility.In order to improve the accuracy of ground truth estimation and avoid the waste of blockchain storage resources and computing resources,an appropriate outlier detection strategy is adopted to process the on-chain data.In the simulation,the effectiveness of the proposed data sharing scheme is proved by a proper ground truth estimation strategy.