Abstract:

In various aspects of monitoring the process of spacecraft testing tasks, such as in orbit fault diagnosis state detection, health state assessment, and spacecraft life prediction, massive test data faces enormous pressure in the transmission, sharing, processing, analysis, storage, and other processes. A distributed big-data publish/subscribe system (BPSS) framework for spacecraft multi-source heterogeneous data management is built. With the help of big-data and cloud platform technology, a set of massive in orbit test data transmission, management, and caching solutions for spacecraft is designed. Master-slave regulation and elastic expansion of cloud nodes are implemented, and large-scale publish/subscribe tasks through dynamic election algorithm are completed based on message consistency. It ensures the security, consistency, and computational efficiency of data transmission, and has the advantages of fast big-data subscription response, high throughput stability of multi-source heterogeneous data, and flexible deployment of distributed components. The results of field spacecraft data management experiments show that the average response delay of BPSS data subscription is 0.05 s/GB. At the same time, when the daily throughput reaches the 85 GB level, the data frame loss rate is controlled at 0.025% and the data damage rate is controlled at 0.018%, which has certain competitiveness compared to other open source publish/subscribe systems.

Key words: cloud platform, distributed, big-data, spacecraft test in orbit, publish/subscribe system