процедура кодування

The paper presents a new method for optimizing data serialization for inter-service communication in distributed systems, called FlagBag. The proposed method aims to reduce the latency of data transmission between services by implementing an efficient data structure organization and serialization algorithm. The study was conducted using Apache Avro as a baseline format for comparison. Experimental results show that FlagBag reduces the average latency of data transmission between services by 18% compared to unmodified Avro, and the amount of transmitted data is reduced by 15% in some cases.

This study focuses on classifying serialization formats used in inter-service communication (ISC) within distributed systems and exploring their historical development. We have examined key features of humanreadable formats such as XML, JSON, and YAML, binary formats like Protocol Buffers and Apache Avro, and columnar formats such as Apache Parquet and ORC, among others. Our results have indicated a significant shift toward binary formats optimized for speed and compactness in recent years.

This study provides an evaluation of the impact of various serialization formats on inter-service communication performance, with a focus on serialization speed, space efficiency, and latency in environments integrating middleware, which are characteristics of microservice architectures. Through an empirical analysis of a wide range of serialization formats and comparison to the traditional standards, it highlights that the compactness of serialized payloads is more critical in reducing end-to-end latency than the sheer speed of serialization itself.

In this research, an analysis of the qualitative characteristics of messages in the Telegram messenger was carried out, which are used as raw data for further analysis of textual content. A thorough review of the parameters of these messages, such as their format, size, presence of noise, and speed. The main goal of the article is to model the optimal approach to saving a large amount of data before the important stage of text analysis. During the research, a detailed analysis of literary sources devoted to this topic was carried out.