Abstract: A parallel data access method for massive remote-sensing images includes: 1) segmenting a remote-sensing image to be processed using a set grid system, data in each grid corresponding to a data block; 2) collecting a data access log of an underlying distributed object storage system Ceph in a past period of time, and measuring a load index of each Ceph cluster and a load index of each pool; 3) selecting a pool with a minimum load in a Ceph cluster with a minimum current load to serve as a storage position of a current data block, and writing each data block into a corresponding pool; 4) returning a data identifier dataid and a data access path of the remote-sensing image; and 5) storing metadata of each data block in a metadata database. The method can support rapid and high-concurrency read and write of large-area data of a grid data block.

Abstract: A parallel data access method for massive remote-sensing images includes: 1) segmenting a remote-sensing image to be processed using a set grid system, data in each grid corresponding to a data block; 2) collecting a data access log of an underlying distributed object storage system Ceph in a past period of time, and measuring a load index of each Ceph cluster and a load index of each pool; 3) selecting a pool with a minimum load in a Ceph cluster with a minimum current load to serve as a storage position of a current data block, and writing each data block into a corresponding pool; 4) returning a data identifier dataid and a data access path of the remote-sensing image; and 5) storing metadata of each data block in a metadata database. The method can support rapid and high-concurrency read and write of large-area data of a grid data block.