Jian-Jia Chen
Tei-Wei Kuo
ABSTRACT
Energy-aware scheduling has received much attention in recent years, especially for systems with serious considerations on energy consumption. While most previous work focuses on the minimization of energy consumption, this paper exploits the maximization of the entire system profit under energy and timing constraints. We propose a greedy approximation algorithm with a 2-approximation ratio. A fully polynomial time approximation scheme (FPTAS) is also proposed, which is an optimal approximation algorithm unless P = NP. For each specified amount of error tolerant to users, the approximation algorithm could provide trade-offs among the specified error, the running time, the approximation ratio, and the memory space complexity. It provides ways for system engineers to trade performance with implementation constraints.
- A. Chandrakasan, S. Sheng, and R. Broderson. Lower-power CMOS digital design. IEEE Journal of Solid-State Circuit, 27(4):473--484, 1992.]]Google Scholar
Cross Ref
- X. Fan, C. S. Ellis, and A. R. Lebeck. Synergy between power-aware memory systems and processor voltage scaling. Technical report, Duke University, November 2002.]]Google Scholar
- M. R. Garey and D. S. Johnson. Computers and intractability: A guide to the theory of NP-completeness. W. H. Freeman and Co, 1979.]] Google ScholarDigital Library
- G. Golub and J. Ortega. Scientific Computing and Differential Equations. Academic Press, 1992.]] Google ScholarDigital Library
- O. H. Ibarra and C. E. Kim. Fast approximation algorithms for the knapsack and sum of subsets problems. Journal of the ACM, 22(4):463--468, 1975.]] Google ScholarDigital Library
- S. Irani, S. Shukla, and R. Gupta. Competitive analysis of dynamic power management strategies for systems with multiple saving states. In Proceedings of the Design Automation and Test Europe Conference, 2002.]] Google ScholarDigital Library
- S. Irani, S. Shukla, and R. Gupta. Algorithms for power savings. In Proceedings of the fourteenth annual ACM-SIAM symposium on Discrete algorithms, pages 37--46. Society for Industrial and Applied Mathematics, 2003.]] Google ScholarDigital Library
- T. Ishihara and H. Yasuura. Voltage scheduling problems for dynamically variable voltage processors. In Proceedings of the 1998 international symposium on Low power electronics and design, pages 179--202, 1998.]] Google ScholarDigital Library
- G. Qu. What is the limit of energy saving by dynamic voltage scaling? In IEEE/ACM International Conference on Computer Aided Design, pages 560--563, 2001.]] Google ScholarDigital Library
- C. Rusu, R. Melhem, and D. Mosse. Maximizing the system profit while satisfiying time and energy constraints. In IEEE 23th Real-Time System Symposium, Dec. 2002.]] Google ScholarDigital Library
- M. Schmitz and B. AI-Hashimi. Considering power variations of DVS processing elements for energy minimisation in distributed systems. In ISSS, 2001.]] Google ScholarDigital Library
- V. V. Vazirani. Approximation Algorithms, chapter 8. Springer, 2001.]] Google ScholarDigital Library
- M. Weiser, B. Welch, A. Demers, and S. Shenker. Scheduling for reduced CPU energy. In Proceedings of Symposium on Operating Systems Design and Implementation, pages 13--23, 1994.]] Google ScholarDigital Library
- F. Yao, A. Demers, and S. Shankar. A scheduling model for reduced CPU energy. In Proceedings of the 36th Annual Symposium on Foundations of Computer Science, pages 374--382. IEEE, 1995.]] Google ScholarDigital Library
- D. Zhu, R. Melhem, and B. Childers. Scheduling with dynamic voltage/speed adjustmenet using slack reclamation in multi-processor real-time systems. In Proceedings of IEEE 22th Real-Time System Symposium, 2001.]] Google ScholarDigital Library
- Profit-driven uniprocessor scheduling with energy and timing constraints
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