Abstract
We propose power-aware on-line task scheduling algorithms for mixed task sets which consist of both periodic and aperiodic tasks. The proposed algorithms utilize the execution behaviors of scheduling servers for aperiodic tasks. Since there is a trade-off between the energy consumption and the response time of aperiodic tasks, the proposed algorithms focus on bounding the response time degradation of aperiodic tasks while they use a more aggressive slack estimation technique for higher energy savings in mixed task sets. We also propose a new slack distribution method which gives better response times with slight energy increases. Experimental results show that the proposed algorithms reduce the energy consumption by 25% and 18% over the non-DVS scheme under the RM scheduling and the EDF scheduling, respectively.
This work was supported by grant No. R01-2001-00360 from the Korea Science & Engineering Foundation and University IT Research Center Project.
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References
Liu, J.W.S.: Real-Time Systems. Prentice Hall, Englewood Cliffs (2000)
Kim, W., Shin, D., Yun, H.-S., Kim, J., Min, S.L.: Performance Comparison of Dynamic Voltage Scaling Algorithms for Hard Real-Time Systems. In: Proc. of IEEE Real-Time and Embedded Technology and Applications Symp., pp. 219–228 (2002)
Shin, Y., Choi, K.: Power Conscious Fixed Priority Scheduling for Hard Real- Time Systems. In: Proc. of Design Automation Conf., pp. 134–139 (1999)
Aydin, H., Melhem, R., Mosse, D., Alvarez, P.M.: Dynamic and Aggressive Scheduling Techniques for Power-Aware Real-Time Systems. In: Proc. of IEEE Real-Time Systems Symp., pp. 95–106 (2001)
Pillai, P., Shin, K.G.: Real-Time Dynamic Voltage Scaling for Low-Power Embedded Operating Systems. In: Proc. of ACM Symp. on Operating Systems Principles, pp. 89–102 (2001)
Kim, W., Kim, J., Min, S.L.: A Dynamic Voltage Scaling Algorithm for Dynamic-Priority Hard Real-Time Systems Using Slack Time Analysis. In: Proc. of Design Automation and Test in Europe, pp. 788–794 (2002)
Strosnider, J.K., Lehoczky, J.P., Sha, L.: The Deferrable Server Algorithm for Enhanced Aperiodic Responsiveness in Hard Real-Time Environments. IEEE Transactions on Computers 44(1), 73–91 (1995)
Sprunt, B., Sha, L., Lehoczky, J.P.: Aperiodic Task Scheduling for Hard Real- Time Systems. Journal of Real-Time Systems 1(1), 27–60 (1989)
Shin, D., Kim, J.: Dynamic Voltage Scaling of Periodic and Aperiodic Tasks in Priority-Driven Systems. In: Proc. of Asia and South Pacific Design Automation Conf. (2004)
Abeni, L., Buttazzo, G.: Integrating Multimedia Applications in Hard Real-Time Systems. In: Proc. of IEEE Real-Time Systems Symp., pp. 4–13 (1998)
Yuan, W., Nahrstedt, K.: Integration of Dynamic Voltage Scaling and Soft Real-Time Scheduling for Open Mobile Systems. In: Proc. of Int. Workshop on Network and Operating Systems Support for Digital Audio and Video, pp. 105–114 (2002)
Doh, Y., Kim, D., Lee, Y.-H., Krishna, C.M.: Constrained Energy Allocation for Mixed Hard and Soft Real-Time Tasks. In: Proc. of Int. Conf. on Real-Time and Embedded Computing Systems and Applications, pp. 533–550 (2003)
Shin, D., Kim, J.: Dynamic Voltage Scaling for Mixed Task Systems in Priority-Driven Systems. Technical report, Computer Architecture and Embedded Systems Laboratory, Seoul National University (2004)
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Shin, D., Kim, J. (2004). Power-Aware Scheduling of Mixed Task Sets in Priority-Driven Systems. In: Yang, L.T., Guo, M., Gao, G.R., Jha, N.K. (eds) Embedded and Ubiquitous Computing. EUC 2004. Lecture Notes in Computer Science, vol 3207. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30121-9_22
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DOI: https://doi.org/10.1007/978-3-540-30121-9_22
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