Energy-Aware Quality of Service Adaptation

In a wide variety of embedded control applications, it is often the energy resources that form the fundamental limits on the system, not the system’s computing capacity. Various techniques have been developed to improve energy efficiency in hardware, such as Dynamic Voltage Scaling (DVS), effectively extending the battery life of these systems. However, a comprehensive mechanism of task adaptation is needed in order to make the best use of the available energy resources, even in the presence of DVS or other power-reducing mechanisms. Further complicating this are the strict timeliness guarantees required by real-time applications commonly found in embedded systems. This paper develops a new framework called Energy-aware Quality of Service (EQoS) that can manage realtime tasks and adapt their execution to maximize the benefits of their computation for a limited energy budget. The concept of an adaptive real-time task and the notion of utility, a measure of the benefit or value gained from their execution, are introduced. Optimal algorithms and heuristics are developed to maximize the utility of the system for a desired system runtime and a given energy budget, and then extended to optimize utility without regard to runtime. We demonstrate the effects of DVS on this system and how EQoS in conjunction with DVS can provide significant gains in utility for fixed energy budgets. Finally, we evaluate this framework through both simulations and experimentation on a working implementation.