A Transition-Aware DVS Method for Jitter-Controlled Real-Time Scheduling

Dynamic voltage scaling (DVS) is a key technique for embedded real-time systems to reduce energy consumption by lowering the supply voltage and operating frequency. Many existing DVS algorithms have to generate the canonical schedules or estimate the lengths of slack time in advance for generating the voltage scaling decisions. Therefore, these methods have to compute the schedules of which the exponential lengths in general. In this paper, we consider a set of jitter-controlled, independents, periodic, hard real-time tasks scheduled according to preemptive pinwheel model. Our approach constructs a tree structure corresponding to a schedule and maintains the data structure at each early-completion point. Our approach consisting off-line and on-line algorithms also considers the effect of transition time and energy. The off-line and on-line algorithm takes O(k+nlogn) and O(k+(p_max/p_min)) time complexity, respectively, where n, k, p_max and p_min denotes the number of jobs, tasks, longest and shortest task period, respectively. Experimental results show that the proposed approach is effective in reducing computational complexity, transition time and energy overhead.