Approximation Algorithms for Multiprocessor Energy-Efficient Scheduling of Periodic Real-Time Tasks with Uncertain Task Execution Time

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 realtime 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.

[1]  Daniel Mossé,et al.  Energy-efficient policies for embedded clusters , 2005, LCTES '05.

[2]  Krzysztof Kuchcinski,et al.  LEneS: task scheduling for low-energy systems using variable supply voltage processors , 2001, ASP-DAC '01.

[3]  Zhiyuan Li,et al.  Energy-Aware Scheduling for Real-Time Multiprocessor Systems with Uncertain Task Execution Time , 2007, 2007 44th ACM/IEEE Design Automation Conference.

[4]  Flavius Gruian.  Hard real-time scheduling for low-energy using stochastic data and DVS processors , 2001, ISLPED '01.

[5]  Kevin Skadron,et al.  Procrastinating voltage scheduling with discrete frequency sets , 2006, Proceedings of the Design Automation & Test in Europe Conference.

[6]  Jian-Jia Chen.  Expected energy consumption minimization in DVS systems with discrete frequencies , 2008, SAC '08.

[7]  J. Vitter,et al.  Approximations with Minimum Packing Constraint Violation , 1992 .

[8]  Hakan Aydin,et al.  Energy-aware task allocation for rate monotonic scheduling , 2005, 11th IEEE Real Time and Embedded Technology and Applications Symposium.

[9]  Tei-Wei Kuo,et al.  An approximation algorithm for energy-efficient scheduling on a chip multiprocessor , 2005, Design, Automation and Test in Europe.

[10]  Tai-Yi Huang,et al.  A Near-optimal Solution for the Heterogeneous Multi-processor Single-level Voltage Setup Problem , 2007, 2007 IEEE International Parallel and Distributed Processing Symposium.

[11]  Alan Jay Smith,et al.  PACE: a new approach to dynamic voltage scaling , 2004, IEEE Transactions on Computers.

[12]  Vijay V. Vazirani,et al.  Approximation Algorithms , 2001, Springer Berlin Heidelberg.

[13]  Rami G. Melhem,et al.  Energy aware scheduling for distributed real-time systems , 2003, Proceedings International Parallel and Distributed Processing Symposium.

[14]  Alexander Schrijver,et al.  Theory of linear and integer programming , 1986, Wiley-Interscience series in discrete mathematics and optimization.

[15]  Tei-Wei Kuo,et al.  Multiprocessor energy-efficient scheduling for real-time tasks with different power characteristics , 2005, 2005 International Conference on Parallel Processing (ICPP'05).

[16]  Tei-Wei Kuo,et al.  Energy-efficient real-time task scheduling with task rejection , 2007 .

[17]  Xiaobo Sharon Hu,et al.  Task scheduling and voltage selection for energy minimization , 2002, DAC '02.

[18]  F. Frances Yao,et al.  A scheduling model for reduced CPU energy , 1995, Proceedings of IEEE 36th Annual Foundations of Computer Science.

[19]  Yung-Hsiang Lu,et al.  Dynamic Voltage Scaling for Multitasking Real-Time Systems With Uncertain Execution Time , 2008, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

[20]  Rami G. Melhem,et al.  A unified practical approach to stochastic DVS scheduling , 2007, EMSOFT '07.

[21]  Kevin Skadron,et al.  Optimal procrastinating voltage scheduling for hard real-time systems , 2005, Proceedings. 42nd Design Automation Conference, 2005..

[22]  Tei-Wei Kuo,et al.  Energy-Efficient Real-Time Task Scheduling with Task Rejection , 2007, 2007 Design, Automation & Test in Europe Conference & Exhibition.

[23]  Tei-Wei Kuo,et al.  Multiprocessor energy-efficient scheduling with task migration considerations , 2004, Proceedings. 16th Euromicro Conference on Real-Time Systems, 2004. ECRTS 2004..

[24]  Klara Nahrstedt,et al.  Energy-efficient soft real-time CPU scheduling for mobile multimedia systems , 2003, SOSP '03.

[25]  Kirk Pruhs,et al.  Dynamic speed scaling to manage energy and temperature , 2004, 45th Annual IEEE Symposium on Foundations of Computer Science.

[26]  Rami G. Melhem,et al.  Minimizing expected energy in real-time embedded systems , 2005, EMSOFT.

[27]  Thomas A. DeMassa,et al.  Digital Integrated Circuits , 1985, 1985 IEEE GaAs IC Symposium Technical Digest.

[28]  Tei-Wei Kuo,et al.  Leakage-Aware Energy-Efficient Scheduling of Real-Time Tasks in Multiprocessor Systems , 2006, 12th IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS'06).

[29]  Sanjoy K. Baruah,et al.  Energy-efficient synthesis of periodic task systems upon identical multiprocessor platforms , 2004, 24th International Conference on Distributed Computing Systems, 2004. Proceedings..

[30]  Tei-Wei Kuo,et al.  Energy-Efficient Real-Time Task Scheduling for a DVS System with a Non-DVS Processing Element , 2006, 2006 27th IEEE International Real-Time Systems Symposium (RTSS'06).

[31]  Qi Yang,et al.  Energy-aware partitioning for multiprocessor real-time systems , 2003, Proceedings International Parallel and Distributed Processing Symposium.

[32]  Krzysztof Kuchcinski,et al.  Uncertainty-based scheduling: energy-efficient ordering for tasks with variable execution time , 2003, ISLPED '03.