Managing real-time constraints through monitoring and analysis-driven edge orchestration

Emerging real-time applications are increasingly moving to distributed heterogeneous platforms, under the promise of more powerful and flexible resource capabilities. This shift inevitably brings new challenges. The design space to deploy chains of threads is more complex, and sound estimates of worst-case execution times are harder to obtain. Additionally, the environment is more dynamic, requiring additional runtime flexibility on the part of the application itself. In this paper, we present an optimization-based approach to this problem. First, we present a model and real-time analysis for modern distributed edge applications. Second, we propose a design-time optimization problem to show how to set the main parameters characterizing such applications from a time-predictability perspective. Then, we present an orchestration and runtime decision-making mechanism that monitors execution times and allows for runtime reconfigurations, spanning from graceful degradation policies to re-distributions of workload. A prototypical implementation of the proposed approach based on the QNX RTOS and its evaluation on a realistic case study based on an edge-based valet parking application conclude the paper.