Research Summary: Deterministic, Explainable and Efficient Stream Processing

Abstract

The vast amounts of data collected and processed by technologies such as Cyber-Physical Systems require new processing paradigms that can keep up with the increasing data volumes. Edge computing and stream processing are two such paradigms that, combined, allow users to process unbounded datasets in an online manner, delivering high-throughput, low-latency insights. Moving stream processing to the edge introduces challenges related to the heterogeneity and resource constraints of the processing infrastructure. In this work, we present state-of-the-art research results that improve the facilities of Stream Processing Engines (SPEs) with data provenance, custom scheduling, and other techniques that can support the usability and performance of streaming applications, spanning through the edge-cloud contexts, as needed.