Minimizing peak temperature in embedded real-time systems via thermal-aware periodic resources
Over the years, thermal-aware designs have become a prominent research issue for real-time application development. A drastic increase in energy consumption of modern processors makes devices running real-time applications more prone to overheating and also decreases the lifespan. As a result, obtaining a reduction in peak temperature is considered the most desirable design aspect in developing such devices as it not only decreases the packaging cost, but also increases the lifetime of a device substantially. In this article, the thermal-aware periodic resource model is proposed which is a proactive scheme for minimizing peak temperature in a system with a microprocessor having basic energy saving features. For this model, polynomial-time algorithms are proposed to determine the lowest processing time (i.e., bandwidth) in periodic intervals with the minimum peak temperature for a specified sporadic task system scheduled by earliest-deadline first (EDF). The proposed algorithms only incur bounded error (based on a user-defined parameter) in determining temperature in exchange for a significant improvement in running time over exact algorithms. Furthermore, we derive the thermal equations to calculate the asymptotic temperature bound for a given thermal-aware periodic resource. These equations, along with the algorithm presented, will give a system designer not only a guarantee of schedulability for a given workload with minimum peak temperature, but also the freedom of choosing a trade-off between the accuracy and the efficiency of the algorithms.
real-time systems thermal-aware scheduling schedulability analysis approximation algorithms