TY - GEN
T1 - Energy-aware scheduling on multiprocessor platforms with devices
AU - Li, Dawei
AU - Wu, Jie
AU - Li, Keqin
AU - Hwang, Kai
PY - 2013
Y1 - 2013
N2 - In this paper, we address the problem of energy-aware task scheduling on DVFS-enabled multiprocessors with DPM-enabled device(s). Given a set of frame-based tasks, we aim to derive a scheduling where the device occupation constraint is respected, all of the tasks meet the shared deadline, and the overall system energy consumption, including energy consumed on both processors and devices, is minimized. For the problem when preemption and migration are allowed, after solving the formulated optimization problem, we regard the tasks that require the same device as a single preemptive task. An Execution Time Filling (ETF) process can be applied to derive a scheduling which adopts the optimal frequency setting; then, we propose Algorithm ETFR, which achieves the optimal system energy consumption, and also Reduces the total number of preemptions and migrations. For the problem when tasks are non-preemptive, we regard the tasks that require the same device as a single non-preemptive task. To assign tasks to processors, we adopt the Worst Fit Decreasing (WFD) strategy using tasks' optimal execution times. After task assignment, we readjust the execution frequency of tasks on each processor, such that the system energy consumption of tasks on each processor is minimized. Various analysis, simulations, and experiments verify the strength of our proposed approaches for the two problems.
AB - In this paper, we address the problem of energy-aware task scheduling on DVFS-enabled multiprocessors with DPM-enabled device(s). Given a set of frame-based tasks, we aim to derive a scheduling where the device occupation constraint is respected, all of the tasks meet the shared deadline, and the overall system energy consumption, including energy consumed on both processors and devices, is minimized. For the problem when preemption and migration are allowed, after solving the formulated optimization problem, we regard the tasks that require the same device as a single preemptive task. An Execution Time Filling (ETF) process can be applied to derive a scheduling which adopts the optimal frequency setting; then, we propose Algorithm ETFR, which achieves the optimal system energy consumption, and also Reduces the total number of preemptions and migrations. For the problem when tasks are non-preemptive, we regard the tasks that require the same device as a single non-preemptive task. To assign tasks to processors, we adopt the Worst Fit Decreasing (WFD) strategy using tasks' optimal execution times. After task assignment, we readjust the execution frequency of tasks on each processor, such that the system energy consumption of tasks on each processor is minimized. Various analysis, simulations, and experiments verify the strength of our proposed approaches for the two problems.
KW - Dynamic power management (DPM)
KW - Dynamic voltage and frequency scaling (DVFS)
KW - Energy-aware scheduling
KW - Execution time filling
KW - System energy consumption
UR - http://www.scopus.com/inward/record.url?scp=84893295570&partnerID=8YFLogxK
U2 - 10.1109/CGC.2013.13
DO - 10.1109/CGC.2013.13
M3 - Conference contribution
AN - SCOPUS:84893295570
SN - 9780769551142
T3 - Proceedings - 2013 IEEE 3rd International Conference on Cloud and Green Computing, CGC 2013 and 2013 IEEE 3rd International Conference on Social Computing and Its Applications, SCA 2013
SP - 26
EP - 33
BT - Proceedings - 2013 IEEE 3rd International Conference on Cloud and Green Computing, CGC 2013 and 2013 IEEE 3rd International Conference on Social Computing and Its Applications, SCA 2013
T2 - 3rd IEEE International Conference on Cloud and Green Computing, CGC 2013, Held Jointly with the 3rd IEEE International Conference on Social Computing and Its Applications, SCA 2013
Y2 - 30 September 2013 through 2 October 2013
ER -