基于遗传算法的电力输变电工程数据存储框架与数据迁移仿真

Data Storage Frame and Data Migration Simulation of Power Transmission and Transformation Engineering Based on Genetic Algorithm

由于电力输变电工程数据多源、异构、迭代更新,需巨大存储空间,且数据挖掘分析难度大,据此本文基于遗传算法设计了分布式数据存储框架与数据迁移。此框架以源数据模型为载体,详细划分电力输变电工程地理信息、三维设计模型、文档资料数据,基于不同数据存储模型,构建了分布式存储框架以进行不同类型数据处理。通过遗传算法可实现海量数据迁移,以不同配置的数据存储中心进行了仿真测试。结果表明,分布式数据存储框架不仅可保障存储效率,还可确保数据完整性与安全性;基于遗传算法的数据迁移可切实解决大量数据存储问题,优化工程数据存储框架综合性能。

Because the data of power transmission and transformation project is multi-source,heterogeneous and iterative,it needs huge storage space,and it is difficult to analyze data mining.This framework takes the source data model as the carrier,divides the power transmission and transformation project geography information,the 3D design model,the document data in detail,based on the different data storage pattern,constructs the distributed storage framework to carry on the different type data processing.The mass data migration can be realized by genetic algorithm,and the simulation test is carried out with different data storage centers.The results show that the distributed data storage framework cannot only guarantee the storage efficiency,but also ensure the data integrity and security.