Utilizing cloud storage architecture for long-pulse fusion experiment data storage

Scientific data storage plays a significant role in research facility. The explosion of data in recent years was always going to make data access, acquiring and management more difficult especially in fusion research field. For future long-pulse experiment like ITER, the extremely large data will be generated continuously for a long time, putting much pressure on both the write performance and the scalability. And traditional database has some defects such as inconvenience of management, hard to scale architecture. Hence a new data storage system is very essential. J-TEXTDB is a data storage and management system based on an application cluster and a storage cluster. J-TEXTDB is designed for big data storage and access, aiming at improving read–write speed, optimizing data system structure. The application cluster of J-TEXTDB is used to provide data manage functions and handles data read and write operations from the users. The storage cluster is used to provide the storage services. Both clusters are composed with general servers. By simply adding server to the cluster can improve the read–write performance, the storage space and redundancy, making whole data system highly scalable and available. In this paper, we propose a data system architecture and data model to manage data more efficient. Benchmarks of J-TEXTDB performance including read and write operations are given.