雾计算中基于多目标优化的数据存储策略研究

Research on Data Storage Strategy Based of Multi-Objective Optimization in Fog Computing

雾计算由性能较弱、更为分散的各种物联网设备组成,这些设备的存储容量和电池容量有限,因此需要一种存储方式对大量的数据进行安全有效地存储。基于此,笔者以数据的请求命中率和能耗为目标,运用多目标优化算法对指定范围内的雾节点数据存储方式进行双目标优化,然后通过自身优化前后对比以及与传统存储算法的能耗和命中比值进行比较,分析得出新存储方式的命中率。

Fog computing is composed of various Internet of things (IOT) devices with weaker performance and more dispersed performance.The storage capacity and battery capacity of these devices are limited,so a storage method is needed to store a large amount of data safely and effectively.Based on this,the author takes the data request hit rate and energy consumption as the goal,uses the multi-objective optimization algorithm to optimize the fog node data storage mode within the specified range,and then compares the energy consumption and hit ratio with the traditional storage algorithm before and after optimization,and analyzes the hit ratio of the new storage method.