Abstract
Dynamic voltage scaling (DVS) is a technique which allows the processors to change speed when executing jobs. Most of the previous works study either single processor or multiple parallel processors. In this paper, we consider a network of DVS enabled processors. Every job needs to go along a certain path in the network and has a certain workload finished on any processor it goes through before it moves on to the next processor. Our objective is to minimize the total energy consumption while finishing every job before its deadline. Due to the intrinsic complexity of this problem, we only focus on line networks with two nodes and a simple one-level tree network (a star). We show that in some of these simple cases, the optimal schedule can be computed efficiently and interleaving is not needed to achieve optimality. However, in both types of networks, how to find the optimal sequence of execution remains a big challenge for jobs with general workloads.
Similar content being viewed by others
References
Albers S (2011) Algorithms for dynamic speed scaling. In: STACS 2011, pp 1–11
Andrews M, Fernandez A, Zhang L, Zhao W (2010) Routing for energy minimization in the speed scaling model. In: Proceedings of 29th IEEE international conference on computer communications, pp 2435–2443
Bansal N, Chan HL, Lam TW, Lee L-K (2008) Scheduling for speed bounded processors. In: Proceedings of the 35th international symposium on automata, languages and programming, pp 409–420
Bansal N, Kimbrel T, Pruhs K (2004) Dynamic speed scaling to manage energy and temperature. In: Proceedings of the 45th annual symposium on foundations of computer science, pp 520–529
Chan HL, Chan WT, Lam TW, Lee LK, Mak KS, Wong PWH (2007) Energy efficient online deadline scheduling. In: Proceedings of the 18th annual ACM-SIAM symposium on discrete algorithms, pp 795–804
Chan WT, Lam TW, Mak KS, Wong PWH (2007) Online deadline scheduling with bounded energy efficiency. In: Proceedings of the 4th annual conference on theory and applications of models of computation, pp 416–427
Garey M, Johnson DS, Sethi R (1976) The complexity of flowshop and jobshop scheduling. Math Oper Res 1:117–129
Graham RL, Lawler EL, Lenstra JK, Rinnooy Kan AHG (1979) Optimization and approximation in deterministic sequencing and scheduling theory: a survey. Ann Discret Math 5:287–326
Hong I, Qu G, Potkonjak M, Srivastavas MB (1998) Synthesis techniques for low-power hard real-time systems on variable voltage processors. In: Proceedings of the IEEE real-time systems, symposium, pp 178–187
Irani S, Pruhs K (2005) Algorithmic problems in power management. ACM SIGACT News 36(2):63–76
Ishihara T, Yasuura H (1998) Voltage scheduling problem for dynamically variable voltage processors. In: Proceedings of international symposium on low power electronics and design, pp 197–202
Johnson SM (1954) Optimal two- and three-stage production schedules with setup times included. Naval Res Logist Q 1:61–68
Kwon W, Kim T (2003) Optimal voltage allocation techniques for dynamically variable voltage processors. In: Proceedings of the 40th conference on design automation, pp 125–130
Lam TW, Lee LK, To IKK, Wong PWH (2007) Energy efficient deadline scheduling in two processor systems. In: Proceedings of the 18th international symposium on algorithm and computation, pp 476–487
Li M, Yao FF (2005) An efficient algorithm for computing optimal discrete voltage schedules. SIAM J Comput 35(3):658–671
Li M, Yao AC, Yao FF (2005) Discrete and continuous min-energy schedules for variable voltage processors. Proc Natl Acad Sci USA 103:3983–3987
Pinedo M (2002) Flow shops and flexible fow shops (deterministic), scheduling: theory, algorithms, and systems (chapter 6), 2nd edn. Prentice Hall, Englewood Cliffs
Pruhs K, Stein C (2010) How to schedule when you have to buy your energy. In: Proceedings of the 13th international workshop on approximation, randomization, and combinatorial optimization. Algorithms and techniques, pp 352–365
Wu W, Li M, Chen E (2009) Min-energy scheduling for aligned jobs in accelerate model. In: Proceedings of the 20th international symposium on algorithms and computation, pp 462–472
Yao F, Demers A, Shenker S (1995) A scheduling model for reduced CPU energy. In: Proceedings of the 36th annual IEEE symposium on foundations of computer science, pp 374–382
Acknowledgments
This work was fully supported by a Grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project No. CityU 124411).
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Mu, Z., Li, M. DVS scheduling in a line or a star network of processors. J Comb Optim 29, 16–35 (2015). https://doi.org/10.1007/s10878-013-9668-y
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10878-013-9668-y