Reliability-conscious energy management for fixed-priority real-time embedded systems with weakly hard QoS-constraint |
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| Affiliation: | 1. West Virginia State University, Institute, WV 25112, U.S.A.;2. California State University, Bakersfield, CA 93311, U.S.A.;3. Tianjin University, Tianjin 300072, China;1. DIEE, University of Cagliari, 09123 Cagliari, Italy;2. PolComIng, University of Sassari, 07100 Sassari, Italy;3. Micrel Lab - DEI, University of Bologna, 40136 Bologna, Italy;1. Dept. of Computer Science, University of California, Los Angeles, United States;2. School of Medicine, Yale University, United States;3. Dept. of Preventative Medicine, Northwestern University, United States;1. Department of Computer Science, Shahid Beheshti University, GC, Tehran, Iran;2. Australian National University, Canberra, ACT 0200, Australia;1. School of computer engineering and science, Shanghai University, Shanghai 200444, China;2. College of Information Science and Engineering, Guilin University of Technology, Guilin 541004, China;1. South China University of Technology, China;2. Shenzhen Institute of Advanced Technology, CAS, China;3. Harbin Institute of Technology, China;4. Southampton University, UK and Guangzhou Institute of Advanced Technology, CAS, China;5. University of Nevada, Las Vegas, USA;6. KTH Royal Institute of Technology, Sweden |
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| Abstract: | Aggressive scaling in technology size has dramatically increased the power density and degraded the reliability of real-time embedded systems. In this paper, we study the problem of reliability-conscious energy minimization for scheduling fixed-priority real-time embedded systems with weakly hard QoS-constraint. The weakly hard QoS-constraint is modeled with (m, k)-constraint, which requires that at least m out of any k consecutive jobs of a task meet their deadlines. We first propose a technique that can balance the static and dynamic energy consumption for real-time jobs with better speed determination than the classical strategies during their feasible intervals. Then based on it, we propose an adaptive fixed-priority scheduling scheme to reduce the energy consumption for the system while preserving its reliability. Through extensive simulations, our experiment results demonstrate that the proposed techniques can significantly outperform the previous research in energy performance while satisfying the weakly hard QoS-constraint under the reliability requirement. |
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