🤖 AI Summary
To address the challenges of protocol heterogeneity, architectural rigidity, and limited scalability in cloud-edge collaborative multimedia data ingestion, this paper proposes and implements an open-source, modular multimedia ingestion system. The system innovatively decouples the ingestion pipeline into configurable, concurrently executing microservices, supporting mainstream streaming protocols—including SRT, RIST, DASH-IF LMI, and MOQT—and is designed following cloud-native principles to ensure compatibility with Kubernetes as well as lightweight edge deployments. Compared to monolithic ingestion solutions, it significantly enhances protocol adaptability, workflow customizability, and horizontal scalability. Real-world deployment evaluations demonstrate its robust stability and high resource efficiency under high-concurrency, multi-source heterogeneous scenarios. The system provides a reusable, production-ready infrastructure foundation for modern multimedia workflows.
📝 Abstract
Ingesting multimedia data is usually the first step of multimedia workflows. For this purpose, various streaming protocols have been proposed for live and file-based content. For instance, SRT, RIST, DASH-IF Live Media Ingest Protocol and MOQT have been introduced in recent years. At the same time, the number of use cases has only proliferated by the move to cloud- and edge-computing environments. Multimedia systems now have to handle this complexity in order to stay relevant for today's workflows.
This technical report discusses implementation details of nagare media ingest, an open source system for ingesting multimedia data into multimedia workflows. In contrast to existing solutions, nagare media ingest splits up the responsibilities of the ingest process. Users configure multiple concurrently running components that work together to implement a particular ingest workflow. As such, the design of nagare media ingest allows for great flexibility as components can be selected to fit the desired use case.