基于增量式流处理的双链区块链多目标优化方法研究

Research on the Multiple Objective Optimization Method of Dual Stranded Blockchain Based on Incremental Stream Processing

针对传统多目标优化方法构建的多目标函数峰值存在误差,导致优化方法的收敛参数数值较小、目标处理数据较少等问题,设计一种基于增量式流处理的双链区块链多目标优化方法。增量聚合双链区块链数据后,计算数据的隶属度,将漂移参数作为多目标的划分尺度。变换处理漂数为一个概率分量,并使用该分量构建并行流处理数据模型,设定划分参数后,输出区块链多目标数据。设定多目标参数约束条件后,构建多目标优化算法,最终完成对双链区块链多目标优化方法的构建。搭建双链区块链支持结构进行对比实验,结果表明:所设计多目标优化方法收敛性参数最大,设计可处理的区块链目标数据更多。

For the traditional multi-objective optimization method,there is an error in the peak value of multi-objective function,which leads to the convergence parameter value of the optimization method being small and the target processing data being small.A double-stranded blockchain multi-objective optimization method based on incremental stream processing is designed.After the incremental aggregation of double-stranded blockchain data,the degree of affiliation of the data is calculated,and the drift parameter is used as a dividing scale for multi-objectives.The transformation processing drift number is a probability component,and the component is used to construct a parallel stream processing data model.After setting the partitioning parameters,the blockchain multi-target data is output.After setting the multi-objective parameter constraints,the multi-objective optimization algorithm is constructed,and the construction of the multi-objective optimization method of the double-stranded blockchain is finally completed.Comparative experiments on the construction of a double-stranded blockchain support structure show that the convergence parameters of the designed multi-objective optimization method are the largest,and the design can handle more blockchain target data.