Optimization Research on Thermal and Power Management for Real-Time Systems

Power consumption issue of real-time system has been paid much attention to by both academia and industry due to its constraints on energy, peak temperature and deadline of real-time task. Up to now, there have been many related researches. Temperature-unaware traditional researches usually adopt DVS to scale processor states for optimal power management. However, with the increasing power density of processors due to the continuous shrinking of chip size, the mutual effect between temperature and power has become unignorably. As a consequence, many new temperature-aware optimization approaches have derived based on the traditional methods. This paper firstly makes an overview of the three models (task, thermal and power) this research bases on; secondly, this paper divides existing researches into two categories: temperature-unaware traditional researches and temperature-aware optimization researches, and the latter one is further divided as single task optimization and multi-task scheduling; thirdly, this paper makes a comparison of the researches from mechanism, optimization goal and effect, and scheduling time etc., analyzing their advantages and disadvantages; finally, this paper points out the future research directions.