云计算环境下基于权重的大数据跨源调度方法研究

Research on Big Data Cross-source Scheduling Method Based on Weight in Cloud Computing Environment

为了提高云计算环境下区块链分片存储资源的跨源调度能力,提出基于权重的大数据跨源调度方法,构建云计算环境下区块链分片存储资源分布结构模型,采用空间多传感信息采样方法进行云计算环境下区块链分片存储资源信息流采样,结合相空间重构方法进行云计算环境下区块链分片存储资源信息结构重组,建立云计算环境下区块链分片存储大数据的特征分解模型,结合分布式网格计算方法进行云计算环境下区块链分片存储资源大数据关联特征提取,结合自适应权重学习方法进行调度的寻优控制,在支持向量机学习模式下实现云计算环境下区块链分片存储资源的大数据跨域调度。仿真结果表明,采用该方法进行云计算环境下区块链分片存储大数据跨域调度的自适应性较好,负载均衡性较强。

In order to improve the cross-source scheduling ability of block chain slicing storage resources in cloud computing environment,a weight-based big data cross-source scheduling method is proposed.The distributed structure model of block chain slicing storage resources in cloud computing environment is constructed,and the spatial multi-sensor information sampling method is used to sample the information flow of block chain sliced storage resources in cloud computing environment.Combined with phase space reconstruction method,the information structure of block chain sliced storage resources in cloud computing environment is reorganized,and the feature decomposition model of block chain slicing storage big data in cloud computing environment is established.Big data association feature extraction of block chain slicing storage resources in cloud computing environment is carried out with distributed grid computing method,and the optimal scheduling control is carried out combined with adaptive weight learning method.Big data cross-domain scheduling of block chain slicing storage resources in cloud computing environment is realized in support vector machine learning mode.The simulation results show that this method has good adaptability and load balancing for block chain slicing storage big data cross-domain scheduling in cloud computing environment.