Optimization of Intelligent Informatization Distributed System for Political Training Support Service based on Flux Architecture
Yanxia Ma · 2022 International Conference on Inventive Computation Technologies (ICICT) · 2022
Optimization of the intelligent informatization distributed system for training support service based on Flux architecture is studied in the paper. Consider that all link failures on the data loop will be indicated as bidirectional link failures. When the source routing protection switching mechanism is used for the loop, if a unidirectional link fails, there will be unnecessary link bandwidth loss, which will reduce the bandwidth utilization of the loop, increase the average service delay, and aggravate the loop congestion. Hence, the Flux architecture will be applied. The existing centralized functional dependency discovery algorithms have the shortcomings of large memory consumption or long computing time, and cannot be well adapted to the distributed big data scenarios, to overcome the mentioned challenges, the Flux is integrated. For testing the robustness, the training support service is selected as the application scenario. The verification is conducted to show the satisfactory performance of the designed model.