Performance-Aware Task Management and Frequency Scaling in Embedded Systems

Due to the dissemination of smartphones and tablets, a constant complexity growth can be observed for both embedded systems and mobile applications. However, this results in an increase in energy consumption. To guarantee longer battery life cycles, it is fundamental to develop system level strategies that allow guaranteeing the applications´ required quality of service by managing the available system resources. In this paper a new task management framework is proposed that controls, in real-time, the execution of multi-threaded applications in order to meet their performance targets. For this, we amend the Linux CFS scheduler decisions to efficiently control the shared resource utilization of parallel applications. The proposed framework relies on runtime performance modelling of both the underlying architecture and the running applications to scale the system resource allocation and frequency. As a result, efficient application execution is achieved not only in terms of performance, but also in energy consumption. Experimental results show that the proposed approach satisfies the applications required performance level by decreasing the relative performance error from 2.801 to 0.168, while achieving 49 % energy savings.