Towards federated learning over large-scale streaming data
Distributed Stream Processing Engines (DSPEs) have seen significant deployment growth along with an increase in streaming data sources such as sensor networks. These DSPEs enable processing large amounts of streaming data in a cluster of commodity machines to extract knowledge and insights in real-time. Due to fluctuating data arrival rates in real-world applications, modern DSPEs often provide auto-scaling. However, the existing designs of advanced analytical frameworks are not effectively aligned with scalable streaming computing environments. We have designed and developed ORCA, a federated ...
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