부산대학교 도서관

Adopting the Fog computing paradigm in traditional Cloud infrastructures reduces latency and optimizes network consumption between data providers and data consumers because the system processes the data closer to its source. However, interoperability issues remain as heterogeneous and distributed data sources with different information models must be accessed for performing Cloud-level processing and analysis. This paper describes an integration architecture based on the OPC UA Aggregation Server paradigm, which introduces Fog-level data processing in industrial automation environments. The proposed architecture allows the creation of a configurable aggregated address space at Fog-level where information from data sources at Edge-level is integrated and served to consumers at Cloud-level. The architecture was tested both to verify that the functional requirements are met, and to analyse the time costs involved in the aggregation of Edge-level servers