In order to manage the metadata of massive spatial data storage effectively, a distributed metadata server management structure based on consistent hashing was introduced, and on this basis, a metadata wheeled backup strategy was proposed in this paper, which stored Hash metadata node after excuting a consistent Hash algorithm according to the method of data backup, and it effectively alleviated the single point of metadata management and access bottleneck problems. Finally testing wheel backup strategy, it obtained the optimum number of metadata node backup solution. Compared with the single point of metadata servers, the proposed strategy improves the metadata safety, reduces the access delay, and improves the load balance of distributed metadata server combined with virtual nodes.

Gravitational Search Algorithm (GSA) easily traps into local optimal solutions and its optimization precision is poor when being applied to function optimization problems. An improved GSA (IGSA) was put forward to solve these problems. It significantly improved the exploration and exploitation abilities of GSA, and had good global and local optimization abilities by introducing opposite learning strategy, elite strategy and boundary mutation strategy. The proposed IGSA had been evaluated on six nonlinear benchmark functions. The experimental results show that, compared with standard GSA, the weighted GSA (WGSA) and Artificial Bee Colony (ABC) algorithms, the IGSA has much better optimization performances in solving various nonlinear functions.