Multi-FDMF: An Agile Management Framework of Multi-domain Data in Decentralized Heterogeneous Environments
Ningchao Ge, Haiwen Chen, Jibing Wu, Ying Hu · 2023
With the in-depth development of big data and artificial intelligence technology, traditional financial, transportation, manufacturing, military and other industries are gradually developing in the direction of digitalization, intelligence and diversification of service scenarios. The transformation of data level is from single-domain data demand to multi-domain data demand. However, the traditional single-domain data management methods are difficult to meet the needs of large-scale multi-domain data management. Aiming at the characteristics of independent autonomy, complex structure and difficult aggregation that are common in distributed heterogeneous environments. This paper puts forward a multi-domain data agile management framework: multi-federated distributed management framework (Multi-FDMF). Based on the idea of "star atom structure" and "federal management institution", the framework realizes the internal federal management of all kinds of data in the field by constructing a local distributed federal system in each "atom" layer. Some "atoms" are linked to the "molecular" center through data channels to form a multi-domain "molecular" external federated system. Finally, multi-federated distributed management of multi-domain data is realized through multiple links at the "molecular" level and above.