Abstract:

[Background] Big Earth data is characterized by its massive scale, diversity, high complexity, and unstructured nature. The data processing faces challenges including heterogeneous datasets, complex computing, and difficulties in collaborative processing. [Objective] This paper aims to improve the efficiency of analyzing, processing, and publishing heterogeneous big earth data, and accelerate scientific innovation. [Methods] This paper designs and implements a novel computing system with a hyper-converged architecture and develops services including computing resource aggregation, job scheduling and HPC functions. These services support integration of cloud computing and supercomputing within a single system. [Results] A Big Earth Data Cloud Service Infrastructure has been established, forming a service of both cloud computing and supercomputing. [Conclusions] The Big Earth Data Cloud Service Infrastructure integrates cloud computing and supercomputing, reduces data transfer between different computing resources, and enhances the efficiency. It meets the needs of SDGs (Sustainable Development Goals), and provides a valuable reference for developing other novel hyper-converged architectures.

Key words: high performance computing, cloud computing, hyper-convergence, big earth data