Speakers: Sanjeev Baskiyar, Department of Computer Science and Software Engineering, Auburn and
                  Tin-Yau Tam

Title: Minimum Energy Consumption for Rate Monotonic Algorithm in a Hard Real-Time Environment

Abstract: Limited battery power is a typical constraint in stand-alone embedded systems. One way to extend the battery lifetime is by reducing CPU power consumption. Because of the quadratic relationship between power consumption in CMOS circuits and CPU voltage, power reduction can be obtained by scaling down supply voltage, or Dynamic Voltage Scaling. However, reducing supply voltage slows down CPU speed since supply voltage has a proportional relationship with CPU frequency. On the other hand, in any real-time embedded environment (especially hard real-time), timing constraints are critical. We focus on dynamic energy reduction of tasks scheduled by Rate Monotonic (RM) algorithm in a hard real-time embedded environment. The RM algorithm preemptively schedules any set of periodic tasks by assigning higher priorities to frequent tasks. For any periodic task set that satisfies the CPU utilization bound, we determine the provably optimal scaling of the worst-case execution time of each task that consumes minimum dynamic energy while satisfying the utilization bound. As RM algorithm is widely used, we expect this work can lead to better energy reduction management and expectations. In this talk we will give the background, formulation, solution, and algorithm of the problem. The talk is based on our paper that appears in the journal Computing.