Abstract
This work deals with the problem to optimise the energy consumption of an embedded system. On system level, tasks are assumed to have a certain CPU-usage they need for completion. Respecting their deadlines, slowing down the task system reduces the energy consumption. For periodically occurring tasks several works exists. But even if jitter comes into account the approaches do not suffice. The event stream model can handle this at an abstract level and the goal of this work is to present and solve the optimisation problem formulated with the event stream model. To reduce the complexity we introduce an approximation to the problem, that allows us a precision/performance trade-off.
This work is supported by the German Research Foundation (DFG), grant GRK 1076/1 and SL 47/3-1.
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References
Ishihara, T., Yasuura, H.: Voltage scheduling problem for dynamically variable voltage processors. In: Proceedings of the International Symposium on Low Power Electronics and Design, pp. 197–202 (1998)
Andrei, A., Schmitz, M., Eles, P., Peng, Z., Al-Hashimi, B.M.: Overhead conscious voltage selection for dynamic and leakage energy reduction of time-constrained systems. In: Proceedings of the Design Automation and Test in Europe Conference (2004)
Hua, S., Qu, G.: Voltage setup problem for embedded systems with multiple voltages. IEEE Transactions on Very Large Scale Integration (VLSI) Systems (2005)
Rong, P., Pedram, M.: Power-aware scheduling and dynamic voltage setting for tasks running on a hard real-time system. In: Proceedings of the Asia and South Pacific Design Automation Conference (2006)
Jejurika, R., Gupta, R.: Optmized slowdown in real-time task systems. In: Proceedings of the 16th Euromicro Conference on Real-Time Systems, pp. 155–164 (2004)
Baruah, S.K., Rosier, L.E., Howell, R.R.: Algorithms and complexity concerning the preemptive scheduling of periodic, real-time tasks on one processor. Real-Time Systems 2(4), 301–324 (1990)
Albers, K., Slomka, F.: An event stream driven approximation for the analysis of real-time systems. In: Proceedings of the Euromicro Conference on Real-Time Systems, pp. 187–195 (2004)
Albers, K., Slomka, F.: Efficient feasibility analysis for real-time systems with edf scheduling. In: Proceedings of the Design Automation and Test in Europe Conference (2005)
Gresser, K.: An event model for deadline verification of hard realtime systems. In: Proceedings of the Fifth Euromicro Workshop on Real Time Systems, pp. 118–123 (1993)
Baruah, S., Chen, D., Gorinsky, S., Mok, A.: Generalized multiframe tasks. Real-Time Systems 17(1), 5–22 (1999)
Lee, T.M., Henkel, J., Wolf, W.: Dynamic runtime re-scheduling allowing multiple implementations of a task for platform-based designs. In: Proceedings of the Design, Automation and Test in Europe Conference (2002)
Tindell, K., Clark, J.: Holistic schedulability analysis for distributed hard real-time systems. Microprocessing and Microprogramming - Euromicro Journal (Special Issue on Parallel Embedded Real-Time Systems) 40(2-3), 117–134 (1994)
Makhorin, A.: GLPK linear programming/MIP solver (2005), http://www.gnu.org/software/glpk/glpk.html
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Lipskoch, H., Albers, K., Slomka, F. (2007). Fast Calculation of Permissible Slowdown Factors for Hard Real-Time Systems. In: Azémard, N., Svensson, L. (eds) Integrated Circuit and System Design. Power and Timing Modeling, Optimization and Simulation. PATMOS 2007. Lecture Notes in Computer Science, vol 4644. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74442-9_48
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DOI: https://doi.org/10.1007/978-3-540-74442-9_48
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