NebulaStream - Data Stream Processing for the Edge-Cloud-Continuum: Course 1
Modern data-driven applications arising in such domains as smart manufacturing, healthcare, and the Internet of Things, pose new challenges to data processing systems. Traditional stream processing systems, such as Flink, Spark, and Kafka Streams are ill-suited to cope with the massive scale of distribution, the heterogeneous computing landscape, and requirements, such as timely processing and actuation. Classical approaches like managed runtimes, interpretation-based query processing, and the optimization of single queries that neglect interactions, greatly limit throughput, latency, energy-efficiency, and the general usability of these systems for emerging applications involving distributed data processing at scale in a sensor-edge-cloud-environment.
Authors
- Volker Markl (ORCID: https://orcid.org/0009-0009-0964-026X)
Institutions
- Technische Universität Berlin (DE)
Publication Details
- Published
- 2025-06-30
- DOI
- https://doi.org/10.1145/3769394.3769415
- Primary Topic
- Scientific Computing and Data Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00