| Resource limited mobile real-time embedded systems can benefit greatly from dynamic adaptation of system parameters. This thesis proposes a novel framework, xTune, that employs iterative tuning using light-weight formal verification at runtime with feedback for dynamic adaptation of mobile real-time embedded systems. One objective of this approach is to enable tradeoff analysis across multiple layers of abstraction (for example, application, middleware, operating system) and predict the possible property violations as the system evolves dynamically over time. Specifically, an executable formal specification is developed for each layer of the mobile real-time system under consideration. The formal specification is then analyzed using statistical model checking and statistical quantitative analysis, to determine the impact of various resource management policies for achieving a variety of end-to-end properties in a quantifiable manner. The integration of formal analysis with dynamic behavior from system execution results in a feedback loop that enables model refinement and further optimization of policies and parameters. Finally, we propose a composition method for coordinated interaction of optimizers at different abstraction layers. The core idea of our approach is that each participating optimizer can restrict its own parameters and exchange refined parameters with its associated layers. We demonstrate the applicability of the proposed methodology to the adaptive provisioning of mobile real-time embedded systems through a multimedia case study on resource-limited mobile devices. |
