Adaptive resource management is critical to ensuring the quality of real-time distributed applications, particularly for energy-constrained mobile handheld devices. In this context, an optimization that simultaneously considers multiple layers (e.g., application, middleware, operating system) needs to be developed for continuous adaptation of system parameters. The tuning of system parameters greatly affects the system's ability to meet QoS requirements, and also directly affects the energy consumption and system robustness. We present a novel approach to developing cross-layer optimization for resource limited real-time distributed systems, based on a constraint refinement technique combined with formal specification and feedback from system implementation. Our approach tunes the parameters in a compositional manner allowing coordinated interaction among sub-layer optimizers that enables holistic cross-layer optimization. We present experiments on a realistic multimedia application which demonstrate that constraint refinement enables us to generate robust and near optimal parameter settings. The constraint language can be used as an interface for composition by encapsulating the details of local optimization algorithms.
['Minyoung Kim', 'Mark-Oliver Stehr', 'Carolyn L. Talcott', 'Nikil Dutt', 'Nalini Venkatasubramanian']
Constraint refinement for online verifiable cross-layer system adaptation