No abstract

In this paper, we address power-aware scheduling of periodic tasks to reduce CPU energy consumption in hard real-time systems through dynamic voltage scaling. Our intertask voltage scheduling solution includes three components: (a) a static (off-line) solution to compute the optimal speed, assuming worst-case workload for each arrival, (b) an online speed reduction mechanism to reclaim energy by adapting to the actual workload, and (c) an on-line, adaptive and speculative speed adjustment mechanism to anticipate early completions of future executions by using the average-case workload information. All these solutions still guarantee that all deadlines are met. Our simulation results show that our reclaiming algorithm alone outperforms other recently proposed inter-task voltage scheduling schemes. Our speculative techniques are shown to provide additional gains, approaching the theoretical lower-bound by a margin of 10%.

Real-time systems are being increasingly used in several applications which are time critical in nature. Fault-tolerance is an important requirement of such systems, due to the catastrophic consequences of not tolerating faults. In this paper, we study a scheme that provides fault-tolerance through scheduling in real-time multiprocessor systems. We schedule multiple copies of dynamic, aperiodic, nonpreemptive tasks in the system, and use two techniques that we call deallocation and overloading to achieve high acceptance ratio (percentage of arriving tasks scheduled by the system). This paper compares the performance of our scheme with that of other fault-tolerant scheduling schemes, and determines how much each of deallocation and overloading affects the acceptance ratio of tasks. The paper also provides a technique that can help real-time system designers determine the number of processors required to provide fault-tolerance in dynamic systems. Lastly, a formal model is developed for the analysis of systems with uniform tasks.

Abstract

In this paper, we provide a n efficient solution for periodic real-time tasks with (potentially) different power consumption characteristics. We show that, a task T, can run a t a constant speed 5';. at every instance without hurting optimality. We sketch an O(n2 log n ) algorithm to compute the optimal S;. values. We also prove that the EDF (Earliest Deadline First) scheduling policy can be used to obtain a feasible schedule with these optimal speed values.