Real-time Management in Emergent Systems

Abstract

Integrating new functionality into complex embedded hard real-time systems requires considerable engineering effort. Emerging formal analysis methodologies and tools from real-time research assist system engineers solving this integration problem. For future organic computer systems, however, it is desirable to integrate these approaches into running systems, enabling them to autonomously perform e.g. online acceptance tests and self-optimization in case of system or environmental changes. This results in high system robustness and extensibility without explicit engineering effort. In this paper, we present an approach adapting formal compositional analysis techniques to realize self-awareness and self-adaptation in embedded systems with respect to real-time properties such as latency constraints, buffer sizes, etc. We introduce a framework for distributed online performance analysis running on embedded real-time systems. Based on this framework we implement an acceptance test for the integration of new functionality into an existing embedded real-time system. Furthermore, we present an online optimization algorithm based on the same framework. In a case study, we demonstrate the applicability of the approach and show that online optimization can increase the acceptance rate with reasonable computational effort.