船舶云计算数据中心高密度信息安全存储方法研究

Research on high density information security storage method in ship cloud computing data center

现有的船舶云计算数据中心高密度信息安全存储方法存在负载均衡性差、存储效率低的难题。为了解决上述问题,提出船舶云计算数据中心高密度信息安全存储方法研究。为了简化信息安全存储的过程,依据压缩感知对高密度信息进行重构,以此为基础,采用遗传迭代查询函数对异常信息进行过滤,得到正常高密度信息,以此为依据,通过P-SLPS算法对高密度信息进行安全存储,实现了船舶云计算数据中心高密度信息的安全存储。通过测试得到,与现有的船舶云计算数据中心高密度信息安全存储方法相比较,提出的船舶云计算数据中心高密度信息安全存储方法极大的提升了负载均衡性与存储效率,充分说明提出的船舶云计算数据中心高密度信息安全存储方法具备更好的存储效果。

The existing high-density information security storage methods of ship cloud computing data center have the problems of poor load balance and low storage efficiency.In order to solve the above problems,this paper proposes a highdensity information security storage method of ship cloud computing data center.In order to simplify the process of information security storage,high-density information is reconstructed based on compressed sensing.On this basis,abnormal information is filtered by genetic iteration query function,and normal high-density information is obtained.On this basis,highdensity information is safely stored by P-SLPS algorithm,and ship cloud meter is realized.The secure storage of high density information in data center.Through testing,compared with the existing high-density information security storage methods of ship cloud computing data center,the proposed high-density information security storage method of ship cloud computing data center greatly improves the load balance and storage efficiency,fully demonstrating the proposed high-density information security storage of ship cloud computing data center.Storage method has better storage effect.