A Cloud Continuum Research Infrastructure for Distributed CPS Experimentation

2026-07-30

AI Summary

This work addresses the challenge that existing experimental environments for distributed Cyber-Physical Systems (CPS) struggle to support reproducible, observable, and controllable integration of heterogeneous edge, fog, and cloud resources. To bridge this gap, the paper proposes a generic cloud continuum experimentation architecture grounded in the SLICES blueprint, featuring a two-layer reference model that decouples infrastructure from application logic. CPS workflows are structured along an edge–fog–cloud continuum, with deployment location, timing, and data provenance treated as core experimental dimensions. The architecture integrates virtualized and physical edge nodes, digital twin coordination, time-windowed control, and combined stream processing with cloud-side aggregation analytics, enabling multi-domain CPS applications to share programmable infrastructure and flexibly deploy and compare control and monitoring strategies. Validation through 40 systematic experiments across geographically distributed deployments—spanning renewable energy community management and AirWatch monitoring use cases—demonstrates the framework’s effectiveness and generality in hybrid physical-virtual settings.

Abstract

Cloud Continuum applications require experimental environments capable of combining heterogeneous Edge, Fog, Cloud, and high-performance computing resources while preserving reproducibility, observability, and control over distributed deployments. This paper presents a two-level reference architecture for Cloud Continuum experimentation built on top of the SLICES Cloud Continuum Blueprint. The proposed approach separates the research-infrastructure layer, which exposes and manages distributed resources, from the application layer, where Cyber-Physical workflows are organized according to an Edge-Fog-Cloud pattern in which placement, timing, and data provenance are treated as first-class experimental concerns. The architecture is designed to support multiple continuum applications rather than a single domain-specific prototype. At the Edge, applications interact with physical devices and perform low-latency sensing or safety actions; at the Fog, they execute near-source coordination, mediation, and stream-processing logic; at the Cloud, they consolidate global knowledge through analytics, optimization, and visualization. This partitioning enables researchers to deploy, customize, and compare alternative control and monitoring strategies over the same programmable infrastructure substrate. The approach is validated through two representative use cases: Renewable Energy Community management, where distributed Digital Twin coordination and time-window-based energy control are requested, and AirWatch, a monitoring pipeline focused on anomaly detection, low-latency alerting, and cloud-side aggregation. Both workloads are evaluated through a systematic campaign of 40 runs comparing virtualized and physical edge deployments over a geographically distributed infrastructure.

Problem

• Cloud Continuum
• Cyber-Physical Systems
• Distributed Experimentation
• Edge-Fog-Cloud
• Research Infrastructure

Innovation

• Cloud Continuum
• Cyber-Physical Systems
• Edge-Fog-Cloud Architecture
• Reproducible Experimentation
• Distributed Resource Management