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Voltage Scheduling

2005; Li, Yao

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Encyclopedia of Algorithms
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Keywords and Synonyms

Dynamic speed scaling          

Problem Definition

This problem is concerned with scheduling jobs with as little energy as possible by adjusting the processor speed wisely. This problem is motivated by dynamic voltage scaling (DVS) (or speed scaling) technique, which enables a processor to operate at a range of voltages and frequencies. Since energy consumption is at least a quadratic function of the supply voltage (hence CPU frequency/speed), it saves energy to execute jobs as slowly as possible while still satisfying all timing constraints. The associated scheduling problem is referred to as min-energy DVS scheduling. Previous work showed that min-energy DVS schedule can be computed in cubic time. The work of Li and Yao [7] considers the discrete model where the processor can only choose its speed from a finite speed set. This work designs an \( O(dn\log n) \) two-phase algorithm to compute the min-energy DVS schedule for the discrete model (drepresents the number of...

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Recommended Reading

  1. Aydin, H., Melhem, R., Mosse, D., Alvarez, P.M.: Determining Optimal Processor Speeds for Periodic Real-Time Tasks with Different Power Characteristics. Euromicro Conference on Real-Time Systems, pp. 225–232. IEEE Computer Society, Washington, DC, USA (2001)

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  2. Bansalm, N., Kimbrel, T., Pruhs, K.: Dynamic Speed Scaling to Manage Energy and Temperature, Proceedings of the 45th Annual IEEE Symposium on Foundations of Computer Science, pp. 520–529. IEEE Computer Society, Washington, DC, USA (2004)

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  3. Burd, T.D., Brodersen, R.W.: Design Issues for Dynamic Voltage Scaling, Proceedings of the 2000 international symposium on Low power electronics and design, pp. 9–14. ACM, New York, USA (2000)

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  4. Chen, J.J., Kuo, T.W., Lu, H.I.: Power-Saving Scheduling for Weakly Dynamic Voltage Scaling Devices Workshop on Algorithms and Data Structures (WADS). LNCS, vol. 3608, pp. 338–349. Springer, Berlin, Germany (2005)

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  5. Irani, S., Pruhs, K.: Algorithmic Problems in Power Management. ACM SIGACT News 36(2), 63–76. New York, NY, USA (2005)

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  6. Kwon, W., Kim, T.: Optimal Voltage Allocation Techniques for Dynamically Variable Voltage Processors. ACM Trans. Embed. Comput. Syst. 4(1), 211–230. New York, NY, USA (2005)

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  7. Li, M., Yao, F.F.: An Efficient Algorithm for Computing Optimal Discrete Voltage Schedules. SIAM J. Comput. 35(3), 658–671. Society for Industrial and Applied Mathematics, Philadelphia, PA, USA (2005)

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  8. Li, M., Yao, A.C., Yao, F.F.: Discrete and Continuous Min-Energy Schedules for Variable Voltage Processors, Proceedings of the National Academy of Sciences USA, 103, pp. 3983–3987. National Academy of Science of the United States of America, Washington, DC, USA (2005)

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  9. Yao, F., Demers, A., Shenker, S.: A Scheduling Model for Reduced CPU Energy, Proceedings of the 36th Annual IEEE Symposium on Foundations of Computer Science, pp. 374–382. IEEE Computer Society, Washington, DC, USA (1995)

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  10. Yun, H.S., Kim, J.: On Energy-Optimal Voltage Scheduling for Fixed-Priority Hard Real-Time Systems. ACM Trans. Embed. Comput. Syst. 2, 393–430. ACM, New York, NY, USA (2003)

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  11. Zhu, D., Melhem, R., Childers, B.: Scheduling with Dynamic Voltage/Speed Adjustment Using Slack Reclamation in Multi-Processor RealTime Systems. Proceedings of the 22nd IEEE Real-Time Systems Symposium (RTSS'01), pp. 84–94. IEEE Computer Society, Washington, DC, USA (2001)

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© 2008 Springer-Verlag

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Li, M. (2008). Voltage Scheduling. In: Kao, MY. (eds) Encyclopedia of Algorithms. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-30162-4_466

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