DEVELOPMENT OF A HIGH-LOAD PIPELINE FOR TRANSFERRING MARINE TRAFFIC DATA FROM SOURCE TO END USER IN REAL TIME
DOI:
https://doi.org/10.34185/1991-7848.itmm.2026.01.064Keywords:
performance optimization, data streaming, maritime traffic, AIS, geographic information system, monitoring, high-load system, .NET, gRPC, RedisAbstract
In modern maritime industry, vessel traffic monitoring is the most important and often required task, where failures in data delivery or instability of software components can lead to colossal economic losses. This paper considers the problem of processing AIS (Automatic Identification System) data streams in large volumes and in real time. The author proposes a pipeline architecture on the .NET platform, with acceleration of object deserialization with source-generated JSON, moving data using gRPC and SignalR with MessagePack, temporary storage of data portions in Redis, and delegating client visualization of results to GPU. The implementation of the subsystem made it possible to achieve a stable display of 20-25 thousand dynamic ship objects – approximately a quarter of the world's maritime traffic – with an instantaneous speed, sometimes outpacing the loading of map tiles. The considered approach can be scaled to other geographic information systems with high data input loads.
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