Dynamic Voltage Scaling for Low-Power Hard Real-Time Systems:Concluding Remarks

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Concluding Remarks

We have described representative DVS techniques proposed for hard real-time systems. Taking advantage of workload variations within a single task execution as well as workload fluctuations from running multiple tasks, DVS provides effective low-power solutions by adjusting the supply voltage, which is a dominant factor in power consumption of embedded systems. In this paper, we focused on two main steps of a DVS algorithm, namely the slack identification step and slack distribution step. We reviewed these steps in two types of voltage scheduling techniques, intra- and intertask DVS.

Intratask DVS techniques identify the slack times due to the early completion of real-time applications and exploit them within a task boundary by lowering the operating clock frequency and supply voltage. Depending on how to identify the slack times and how to select the voltage scaling points, different kinds of IntraDVS techniques have been introduced. The intratask slack times can be identified by observing the execution path or the run-time architectural events (such as memory stall). The energy efficiency of IntraDVS techniques is affected significantly depending on how accurately the techniques can predict the future workload. Using the profile information of task executions, for example, may give a more efficient IntraDVS algorithm. Since IntraDVS changes the supply voltage in a fine granularity, IntraDVS techniques require to consider the voltage scaling overhead. In addition, the available voltage levels should be taken into account in scaling the voltage level.

Intertask DVS addresses energy reduction at the task group level. Hard real-time systems can benefit from intertask DVS, while maintaining their real-time behavior. The majority of hard real-time interDVS techniques build upon classic real-time scheduling strategies in order to fulfill their timing requirements. Such techniques, ranging from fully off line to run time, are based on accurately estimating the slack time and efficiently distributing it to instances. Intertask DVS mechanisms are orthogonal to intratask techniques, and are often used in conjunction with the latter. Nevertheless, overly complex DVS approaches may introduce overheads that cancel out the energy gains, depending on the processor, application, and the mechanisms involved.

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