Data Analysis Verifiable Computing Platform Based On Blockchain

With the rapid development of computer technology,in order to meet the increasing demand of data resources,it is the development trend of information technology to share and distribute the massive data resources.However,there are still many security problems in the storage,data analysis and calculation processing of open data resources.For example,in the system of open access journals,as the scale of journal data increases,under the premise of ensure the safety storage of paper text data,how to implement the correct analysis of the paper text data in order to meet the people's demand for obtaining effective information quickly and accurately from the massive text data is an urgent problem to be solved by the current open access journal system.Facing the open distributed system,blockchain technology is a secure basic computing technology,and verifiable computing is an effective mechanism to solve the correctness of outsourced computing.Running verifiable computing on blockchain will be a reliable computing method to solve the security problems of open data storage and distributed computing processing.To solve the above problems,this paper designs a data analysis verifiable computing platform.The platform architecture is divided into three layers: data access layer,data analysis and verification computing layer and user application layer.Facing the open access journal application,the data access layer can store the paper data,the data analysis and verification calculation layer can analyze the paper text data,and the user application layer is used to realize the interaction between the platform and the user.In order to ensure the security of data storage and the correctness of analysis results,this paper applies block chain technology and verifiable computing technology to the process of text data analysis and calculation,and proposes a platform of data analysis and verifiable computing based on blockchain.The data analysis server nodes in this scheme will complete the calculation and verification tasks in turn according to the smart contract,and reach the consistency of the calculation results among nodes according to the consensus of the blockchain.In order to optimize the platform,this paper conducted an in-depth analysis,build a data analysis verifiable calculation model based on blockchain and the specific calculation tasks,verification tasks,and steps of the PBFT consensus(Practical Byzantine fault tolerance)process of the data analysis server node in the platform solution are calculated and optimized.Finally,a resource optimization method for transaction throughput based on energy consumption is given,and the simulation results show that this optimization method can improve platform preliminary transaction throughput.In order to further solve the scalability problem of data analysis verifiable computing platform based on blockchain,combination with sharding technology,a scalable scheme of data analysis verifiable computing platform based on sharding technology is proposed.By using the sharding technology,the data analysis server nodes in the original platform are randomly allocated to multiple shards,so the original platform is expanded from single shard to multiple shards,and the scalability problem of the original platform is solved effectively.On this basis,this paper analyzes the computing resources and energy consumption of the consensus computing process in the proposed platform scalability scheme,and given the platform throughput optimization strategy based on energy consumption and reasonable number of shards.The simulation results show that the proposed scheme of data analysis verifiable computing platform based on the sharding technology combined with the optimization strategy can effectively solve the scalability problem of the original platform.Finally,according to the above design scheme,a data analysis verifiable computing platform for journal papers is implemented.Furthermore,the hierarchy of the platform and the processing flow between each hierarchy are elaborated in detail.At the same time,according to the established analysis model and optimization method and combined with the actual scene,the platform of journal paper data collection,paper text data keyword extraction model update and verification of the specific process is implemented and optimized.