• Computer Science > Distributed, Parallel, and Cluster Computing [Submitted on 19 Feb 2026] Title:Visual Insights into Agentic Optimization of Pervasive Stream Processing Services View PDF HTML (experimental)Abstract:Processing sensory data close to the data source, often involving Edge devices, promises low latency for pervasive applications, like smart cities. • This commonly involves a multitude of processing services, executed with limited resources; this setup faces three problems: first, the application demand and the resource availability fluctuate, so the service execution must scale dynamically to sustain processing requirements (e.g., latency); second, each service permits different actions to adjust its operation, so they require individual scaling policies; third, without a higher-level mediator, services would cannibalize any resources of services co-located on the same device. • This demo first presents a platform for context-aware autoscaling of stream processing services that allows developers to monitor and adjust the service execution across multiple service-specific parameters. • We then connect a scaling agent to these interfaces that gradually builds an understanding of the processing environment by exploring each service’s action space; the agent then optimizes the service execution according to this knowledge. • Participants can revisit the demo contents as video summary and introductory poster, or build a custom agent by extending the artifact repository.
Article Summaries:
- Computer Science > Distributed, Parallel, and Cluster Computing [Submitted on 19 Feb 2026] Title:Visual Insights into Agentic Optimization of Pervasive Stream Processing Services View PDF HTML (experimental)Abstract:Processing sensory data close to the data source, often involving Edge devices, promises low latency for pervasive applications, like smart cities. This commonly involves a multitude of processing services, executed with limited resources; this setup faces three problems: first, the application demand and the resource availability fluctuate, so the service execution must scale dyna
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