Research on Scientific Research Data Platform Based on Big Data

Abstract

In order to realize the fault tolerance of real-time tasks in scientific research data platform information platform, based on adaptive feedback equalization and symbol modulation technology, a fault-tolerant scheduling model of real-time tasks in scientific research data platform information is proposed in the paper. What is more, the platform transmission channel model of the scientific research data platform information under routing conflicts is first constructed to optimize the information transmission protocol of the scientific research data platform. Secondly, the fuzzy C-means clustering method is applied to perform the inspection robot information fusion. Meanwhile, the symbol modulation method is used for fault-tolerant scheduling of real-time tasks in the information platform. Finally, a simulation experiment is carried out. The results show that the method proposed in the paper has better fault tolerance for platform real-time task scheduling of scientific research data platform information, and the channel balance of the information platform is stronger, which improves the platform real-time task scheduling capability of scientific research data platform information.