a constraint-based application model and scheduling techniques for power-aware systems
New embedded systems must be power-aware , not just low-power. That is, they must track their power sources and the changing power and performance constraints imposed by the environment. Moreover, they must fully explore and integrate many novel power management techniques. Unfortunately, these techniques are often incompatible with each other due to overspecialized formulations or they fail to consider system-wide issues. This paper proposes a new graph-based model to integrate novel power management techniques and facilitate design-space exploration of power-aware embedded systems. It captures min/max timing and min/max power constraints on computation and non-computation tasks through a new constraint classification and enables derivation of flexible system-level schedules. We demonstrate the effectiveness of this model with a power-aware scheduler on real mission-critical applications. Experimental results show that our automated techniques can improve performance and reduce energy cost simultaneously. The application model and scheduling tool presented in this paper form the basis of the IMPACCT system-level framework that will enable designers to aggressively explore many power-performance trade-offs with confidence.
constraint applications model scheduling power-aware power systems embedded systems tracking performance environments exploration integrability paper timing computation classification flexibility demonstrate effect experimentation automation energy cost tool  framework  power-aware real-time scheduling embedded systems software constraint modeling design space exploration system-level design low power graph critic power-management