2008 IEEE Real-Time and Embedded Technology and Applications Symposium Approximation Algorithms for Multiprocessor Energy-Efficient Scheduling of Periodic Real-Time Tasks with Uncertain Task Execution Time April 22-April 24 ISBN: 978-0-7695-3146-5
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/RTAS.2008.24
Energy-efficiency has been an important system issue in hardware and software designs for both real-time embedded systems and server systems.??This research explores systems with probabilistic distribution on the execution time of real-time tasks on homogeneous multiprocessor platforms with the capability of dynamic voltage scaling (DVS). The objective is to derive a task partition which minimizes the expected energy consumption for completing all the given tasks in time.??We give an efficient 1.13-approximation algorithm and a polynomial-time approximation scheme (PTAS) to provide worst-case guarantees for the strongly NP-hard problem. Experimental results show that the algorithms can effectively minimize the expected energy consumption.
Index Terms:
Dynamic Voltage Scaling (DVS), Multiprocessor Scheduling, Probability, Expected Energy Consumption Minimization, Energy-Efficient Scheduling
Citation:
Jian-Jia Chen, Chuan-Yue Yang, Hsueh-I Lu, Tei-Wei Kuo, "Approximation Algorithms for Multiprocessor Energy-Efficient Scheduling of Periodic Real-Time Tasks with Uncertain Task Execution Time," rtas, pp.13-23, 2008 IEEE Real-Time and Embedded Technology and Applications Symposium, 2008 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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