Distributed System Optimization Analysis Based on Data Fusion and Data Transmission Method

Abstract

With the continuous development of network technology and the release of various software products, people's lives are increasingly connected with the Internet. With the rapid increase in the number of users of software products, the processing requirements of servers are also increasing rapidly, and distributed systems begin to play an important role. The purpose of this paper is to analyze the optimization of distributed systems based on data fusion and transmission methods. First, it reveals the research and development background of the subject and its importance in scientific research, and studies the data acquisition technology based on RabbitMQ. Some new RabbitMQ implementation functions are proposed in the log collection service, and the RabbitMQ message processing method inside the model is analyzed and optimized. After comparative experiments in this paper, it is confirmed that the optimized RabbitMQ can support more log generators and thus have more efficient processing performance. Through experimental comparison and data analysis, it can be found that in this use case, when there is only one producer, the maximum delivery speed of the server before optimization can be reached faster, with a speed of 3800msg/s, while the optimized server with the maximum delivery speed is 3950msg/s, 2.3% higher than the highest delivery speed.