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This paper presents an adaptive data delivery method for data science pipelines. While this method is feasible for processes communicating over any network, in this work we focus on edge-fog-cloud infrastructures. In a diagnostic phase, a model based on the Bernoulli principle is used to create a representation of bottlenecks in a pipeline. In a supervision phase, a watchman/sentinel cooperative system monitors the throughput of the pipeline stages to create a bottleneck-stage scheme. In a rectification phase, this system produces replicas of bottlenecks stages, mitigating the workload congestion using implicit parallelism and load balancing algorithms. This method is automatically and transparently invoked to produce a steady continuum dataflow. To test our proposal, we conducted a case study about the processing of medical and satellite data. The evaluation revealed that this method creates continuum …