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Energy Conscious Scheduling for Distributed Computing Systems under Different Operating Conditions
August 2011 (vol. 22 no. 8)
pp. 1374-1381
ASCII Text
x 
 
Young Choon Lee, Albert Y. Zomaya, "Energy Conscious Scheduling for Distributed Computing Systems under Different Operating Conditions," IEEE Transactions on Parallel and Distributed Systems, vol. 22, no. 8, pp. 1374-1381, August, 2011.
 
 
BibTex
x
 
@article{ 10.1109/TPDS.2010.208,
author = {Young Choon Lee and Albert Y. Zomaya},
title = {Energy Conscious Scheduling for Distributed Computing Systems under Different Operating Conditions},
journal ={IEEE Transactions on Parallel and Distributed Systems},
volume = {22},
number = {8},
issn = {1045-9219},
year = {2011},
pages = {1374-1381},
doi = {http://doi.ieeecomputersociety.org/10.1109/TPDS.2010.208},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Parallel and Distributed Systems
TI - Energy Conscious Scheduling for Distributed Computing Systems under Different Operating Conditions
IS - 8
SN - 1045-9219
SP1374
EP1381
EPD - 1374-1381
A1 - Young Choon Lee,
A1 - Albert Y. Zomaya,
PY - 2011
KW - Computer systems organization
KW - energy-aware systems
KW - scheduling and task partitioning
KW - simulation of multiprocessor systems
KW - multicomputer systems
KW - performance of systems.
VL - 22
JA - IEEE Transactions on Parallel and Distributed Systems
ER -
 
Young Choon Lee, University of Sydney, Sydney
Albert Y. Zomaya, University of Sydney, Sydney
Traditionally, the primary performance goal of computer systems has focused on reducing the execution time of applications while increasing throughput. This performance goal has been mostly achieved by the development of high-density computer systems. As witnessed recently, these systems provide very powerful processing capability and capacity. They often consist of tens or hundreds of thousands of processors and other resource-hungry devices. The energy consumption of these systems has become a major concern. In this paper, we address the problem of scheduling precedence-constrained parallel applications on multiprocessor computer systems and present two energy-conscious scheduling algorithms using dynamic voltage scaling (DVS). A number of recent commodity processors are capable of DVS, which enables processors to operate at different voltage supply levels at the expense of sacrificing clock frequencies. In the context of scheduling, this multiple voltage facility implies that there is a trade-off between the quality of schedules and energy consumption. To effectively balance these two performance goals, we have devised a novel objective function and a variant from that. The main difference between the two algorithms is in their measurement of energy consumption. The extensive comparative evaluations conducted as part of this work show that the performance of our algorithms is very compelling in terms of both application completion time and energy consumption.

[1] Y.C. Lee and A.Y. Zomaya, Scheduling in Grid Environments, Handbook of Parallel Computing: Models, Algorithms and Applications, S. Rajasekaran and J. Reif, eds, pp. 21.1-21.19. CRC Press, 2008.
[2] V. Venkatachalam and M. Franz, "Power Reduction Techniques for Microprocessor Systems," ACM Computing Survey, vol. 37, no. 3, pp. 195-237, 2005.
[3] Y. Tian, J. Boangoat, E. Ekici, and F. Ozguner, "Real-Time Task Mapping and Scheduling for Collaborative In-Network Processing in DVS-Enabled Wireless Sensor Networks," Proc. Int'l Parallel and Distributed Processing Symp. (IPDPS '06), 2006.
[4] K.H. Kim, R. Buyya, and J. Kim, "Power Aware Scheduling of Bag-of-Tasks Applications with Deadline Constraints on DVS-Enabled Clusters," Proc. Seventh IEEE Int'l Symp. Cluster Computing and the Grid (CCGrid '07), May 2007.
[5] D.P. Bunde, "Power-Aware Scheduling for Makespan and Flow," Proc. 18th Ann. ACM Symp. Parallelism in Algorithms and Architectures, July 2006.
[6] D. Zhu, R. Melhem, and B.R. Childers, "Scheduling with Dynamic Voltage/Speed Adjustment Using Slack Reclamation in Multiprocessor Realtime Systems," IEEE Trans. Parallel and Distributed Systems, vol. 14, no. 7, pp. 686-700, July 2003.
[7] R. Ge, X. Feng, and K.W. Cameron, "Performance-Constrained Distributed DVS Scheduling for Scientific Applications on Power-Aware Clusters," Proc. ACM/IEEE Conf. Supercomputing (SC '05), pp. 34-44, Nov. 2005.
[8] X. Zhong and C.-Z. Xu, "Energy-Aware Modeling and Scheduling for Dynamic Voltage Scaling with Statistical Realtime Guarantee," IEEE Trans. Computers, vol. 56, no. 3, pp. 358-372, Mar. 2007.
[9] S. Darbha and D.P. Agrawal, "Optimal Scheduling Algorithm for Distributed-Memory Machines," IEEE Trans. Parallel and Distributed Systems, vol. 9, no. 1, pp. 87-95, Jan. 1998.
[10] A.Y. Zomaya, C. Ward, and B.S. Macey, "Genetic Scheduling for Parallel Processor Systems: Comparative Studies and Performance Issues," IEEE Trans. Parallel and Distributed Systems, vol. 10, no. 8, pp. 795-812, Aug. 1999.
[11] H. Topcuouglu, S. Hariri, and M.-Y. Wu, "Performance-Effective and Low-Complexity Task Scheduling for Heterogeneous Computing," IEEE Trans. Parallel and Distributed Systems, vol. 13, no. 3, pp. 260-274, Mar. 2002.
[12] Y.C. Lee and A.Y. Zomaya, "A Novel State Transition Method for Metaheuristic-Based Scheduling in Heterogeneous Computing Systems," IEEE Trans. Parallel and Distributed Systems, vol. 19, no. 9, pp. 1215-1223, Sept. 2008.
[13] B. Rountree, D.K. Lowenthal, S. Funk, V.W. Freeh, B.R. de Supinski, and M. Schulz, "Bounding Energy Consumption in Large-Scale MPI Programs," Proc. ACM/IEEE Conf. Supercomputing, Nov. 2007.
[14] J.G. Koomey, "Estimating Total Power Consumption by Servers in the U.S. and the World," 2009.
[15] G. Koch, "Discovering Multi-Core: Extending the Benefits of Moore's Law," Technology@Intel Magazine, http://www.intel. com/technology/magazine/ computingmulti-core-0705.pdf, July 2005.
[16] Y.C. Lee and A.Y. Zomaya, "Minimizing Energy Consumption for Precedence-Constrained Applications Using Dynamic Voltage Scaling," Proc. Int'l Symp. Cluster Computing and the Grid (CCGRID '09), pp. 92-99, May 2009.
[17] Intel, Intel Pentium M Processor Datasheet, 2004.
[18] R. Min, T. Furrer, and A. Chandrakasan, "Dynamic Voltage Scaling Techniques for Distributed Microsensor Networks," Proc. IEEE Workshop Very Large Scale Integration, pp. 43-46, Apr. 2000.
[19] M.R. Garey and D.S. Johnson, Computers and Intractability: A Guide to the Theory of NP-Completeness, pp. 238-239. W.H. Freeman and Co., 1979.
[20] D. Bozdag, U. Catalyurek, and F. Ozguner, "A Task Duplication Based Bottom-Up Scheduling Algorithm for Heterogeneous Environments," Proc. Int'l Parallel and Distributed Processing Symp. (IPDPS '05), Apr. 2005.
[21] J.J. Chen and T.W. Kuo, "Multiprocessor Energy-Efficient Scheduling for RealTime Tasks with Different Power Characteristics," Proc. Int'l Conf. Parallel Processing (ICPP '05), pp. 13-20, 2005.
[22] K. Choi, R. Soma, and M. Pedram, "Fine-Grained Dynamic Voltage and Frequency Scaling for Precise Energy and Performance Tradeoff Based on the Ratio of Off-Chip Access to On-Chip Computation Times," IEEE Trans. Computer-Aided Design of Integrated Circuits and Systems, vol. 24, no. 1, pp. 18-28, Jan. 2005.
[23] A. Weissel and F. Bellosa, "Process Cruise Control," Proc. Conf. Compilers, Architecture and Synthesis for Embedded Systems, pp. 238-246, 2002.
[24] A. Miyoshi, C. Lefurgy, E.V. Hensbergen, R. Rajamony, and R. Rajkumar, "Critical Power Slope: Understanding the Runtime Effects of Frequency Scaling," Proc. 16th Int'l Conf. Supercomputing, pp. 35-44, 2002.
[25] D. Zhu, D. Mosse, and R. Melhem, "Power-Aware Scheduling for AND/OR Graphs in Realtime Systems," IEEE Trans. Parallel and Distributed Systems, vol. 15, no. 9, pp. 849-864, Sept. 2004.
[26] M.-Y. Wu and D.D. Gajski, "Hypertool: A Programming Aid for Message-Passing Systems," IEEE Trans. Parallel and Distributed Systems, vol. 1, no. 3, pp. 330-343, July 1990.
[27] R.E. Lord, J.S. Kowalik, and S.P. Kumar, "Solving Linear Algebraic Equations on an MIMD Computer," J. ACM, vol. 30, no. 1, pp. 103-117, Jan. 1983.
[28] T.H. Cormen, C.E. Leiserson, and R.L. Rivest, Introduction to Algorithms. MIT Press, 1990.
[29] S.C. Kim, S. Lee, and J. Hahm, "Push-Pull: Deterministic Search-Based DAG Scheduling for Heterogeneous Cluster Systems," IEEE Trans. Parallel and Distributed Systems, vol. 18, no. 11, pp. 1489-1502, Nov. 2007.

Index Terms:
Computer systems organization, energy-aware systems, scheduling and task partitioning, simulation of multiprocessor systems, multicomputer systems, performance of systems.
Citation:
Young Choon Lee, Albert Y. Zomaya, "Energy Conscious Scheduling for Distributed Computing Systems under Different Operating Conditions," IEEE Transactions on Parallel and Distributed Systems, vol. 22, no. 8, pp. 1374-1381, Aug. 2011, doi:10.1109/TPDS.2010.208
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