On the Problem of Developing a Fault-Tolerant High-Loaded Cluster of Support for an Intelligent Transportation System

The study considers methods and means of constructing architectures of big data processing systems for intelligent transportation systems. When developing a large intelligent transportation system (for example, within a large city, region or country), there are issues including redundancy and duplication of stored data. The purpose of this paper is to improve the performance of big data processing system for intelligent transportation system. The work gives an overview of the main approaches and tools for solving problems of development of systems for processing big data, in particular, we considered the conceptual apparatus in the field of ongoing research, analyzed the practical approaches to the distributed storage and processing of big data, and reviewed the theoretical basis of the functioning of data lakes. Also, the work carried out the development of a prototype software system for processing big data for intelligent transport system, in particular, the proposed methodology for building a decentralized ITS, describing the main implemented services, as well as testing the prototype software.