Energy consumption has become a key metric for evaluating how good an embedded system is,alongside more performance metrics like respecting operation deadlines and speed of execution.Schedulability improvement is no l...Energy consumption has become a key metric for evaluating how good an embedded system is,alongside more performance metrics like respecting operation deadlines and speed of execution.Schedulability improvement is no longer the only metric by which optimality is judged.In fact,energy efficiency is becoming a preferred choice with a fundamental objective to optimize the system's lifetime.In this work,we propose an optimal energy efficient scheduling algorithm for aperiodic real-time jobs to reduce CPU energy consumption.Specifically,we apply the concept of real-time process scheduling to a dynamic voltage and frequency scaling(DVFS)technique.We address a variant of earliest deadline first(EDF)scheduling algorithm called energy saving-dynamic voltage and frequency scaling(ES-DVFS)algorithm that is suited to unpredictable future energy production and irregular job arrivals.We prove that ES-DVFS cannot attain a total value greater than C/ˆSα,whereˆS is the minimum speed of any job and C is the available energy capacity.We also investigate the implications of having in advance,information about the largest job size and the minimum speed used for the competitive factor of ES-DVFS.We show that such advance knowledge makes possible the design of semi-on-line algorithm,ES-DVFS∗∗,that achieved a constant competitive factor of 0.5 which is proved as an optimal competitive factor.The experimental study demonstrates that substantial energy savings and highest percentage of feasible job sets can be obtained through our solution that combines EDF and DVFS optimally under the given aperiodic jobs and energy models.展开更多
The growth of environmental energy harvesting has been explosive in wireless computing systems especially when replacing or recharging batteries manually is impracticable.This work investigates the scheduling of perio...The growth of environmental energy harvesting has been explosive in wireless computing systems especially when replacing or recharging batteries manually is impracticable.This work investigates the scheduling of periodic weekly hard real-time tasks under energy constraints.Based on this motivation,we proposed a real-time scheduling algorithm,namely energy guarantee dynamic voltage and frequency scaling(EG-DVFS),that utilizes the earliest deadline-harvesting(ED-H)scheduling algorithm combined with dynamic voltage and frequency scaling.This one is qualified as real-time since tasks must satisfy their timing constraints.We assume that the preemptable tasks receive dynamic priorities according to the earliest deadline first(EDF)rule.EG-DVFS adjusts the processor's behavior by characterizing the properties of the energy source module,capacity of the stored energy as well as the harvested energy in a future duration.Specifically,tasks are executed at full processor speed if the amount of energy in the battery is enough to finish its execution.Otherwise,the processor slows down task execution to the lowest possible processor speed while still guaranteeing to meet all the timing constraints.EG-DVFS mainly depends on the on-line computation of the slack time and the slack energy with dynamic voltage and frequency selection in order to achieve an improved system performance.Experimental results show that EG-DVFS can achieve capacity savings up of up to 33%when compared to ED-H.展开更多
文摘Energy consumption has become a key metric for evaluating how good an embedded system is,alongside more performance metrics like respecting operation deadlines and speed of execution.Schedulability improvement is no longer the only metric by which optimality is judged.In fact,energy efficiency is becoming a preferred choice with a fundamental objective to optimize the system's lifetime.In this work,we propose an optimal energy efficient scheduling algorithm for aperiodic real-time jobs to reduce CPU energy consumption.Specifically,we apply the concept of real-time process scheduling to a dynamic voltage and frequency scaling(DVFS)technique.We address a variant of earliest deadline first(EDF)scheduling algorithm called energy saving-dynamic voltage and frequency scaling(ES-DVFS)algorithm that is suited to unpredictable future energy production and irregular job arrivals.We prove that ES-DVFS cannot attain a total value greater than C/ˆSα,whereˆS is the minimum speed of any job and C is the available energy capacity.We also investigate the implications of having in advance,information about the largest job size and the minimum speed used for the competitive factor of ES-DVFS.We show that such advance knowledge makes possible the design of semi-on-line algorithm,ES-DVFS∗∗,that achieved a constant competitive factor of 0.5 which is proved as an optimal competitive factor.The experimental study demonstrates that substantial energy savings and highest percentage of feasible job sets can be obtained through our solution that combines EDF and DVFS optimally under the given aperiodic jobs and energy models.
文摘The growth of environmental energy harvesting has been explosive in wireless computing systems especially when replacing or recharging batteries manually is impracticable.This work investigates the scheduling of periodic weekly hard real-time tasks under energy constraints.Based on this motivation,we proposed a real-time scheduling algorithm,namely energy guarantee dynamic voltage and frequency scaling(EG-DVFS),that utilizes the earliest deadline-harvesting(ED-H)scheduling algorithm combined with dynamic voltage and frequency scaling.This one is qualified as real-time since tasks must satisfy their timing constraints.We assume that the preemptable tasks receive dynamic priorities according to the earliest deadline first(EDF)rule.EG-DVFS adjusts the processor's behavior by characterizing the properties of the energy source module,capacity of the stored energy as well as the harvested energy in a future duration.Specifically,tasks are executed at full processor speed if the amount of energy in the battery is enough to finish its execution.Otherwise,the processor slows down task execution to the lowest possible processor speed while still guaranteeing to meet all the timing constraints.EG-DVFS mainly depends on the on-line computation of the slack time and the slack energy with dynamic voltage and frequency selection in order to achieve an improved system performance.Experimental results show that EG-DVFS can achieve capacity savings up of up to 33%when compared to ED-H.
