Reliability-aware low energy scheduling in real time systems with shared resources |
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| Affiliation: | 1. CEA, LIST, Laboratory of Model Driven Engineering for Embedded Systems, P.C. 174, Gif-sur-Yvette 91191, France;2. CEA, LIST, Software Reliability and Security Laboratory, P.C. 174, Gif-sur-Yvette 91191, France;3. Faculty of Computers and Information, Menofia University, Egypt;1. State Key Laboratory of Integrated Service Networks, Xidian University, Xi''an, China;2. Department of Computer Science, University of Otago, Dunedin, New Zealand;3. Science and Technology on Information Transmission and Dissemination in Communication Networks Laboratory, Shijiazhuang 050081, China;1. Eindhoven University of Technology, The Netherlands;2. Topic Embedded Products, The Netherlands;1. Convergence Laboratory, KT R&D Center, 151 Taebong-ro, Seocho-gu, Seoul 06763, Korea;2. Department of Computer Science and Engineering, Soongsil University, 369 Sangdo-Ro, Dongjak-gu, Seoul 156-743, Korea;3. Department of Computer Science and Engineering, Seoul National University of Science and Technology (SeoulTech), 232 Gongneung-ro, Nowon-gu, Seoul, 01811, Korea |
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| Abstract: | Dynamic voltage scaling (DVS) is a technique which is widely used to save energy in a real time system. Recent research shows that it has a negative impact on the system reliability. In this paper, we consider the problem of the system reliability and focus on a periodic task set that the task instance shares resources. Firstly, we present a static low power scheduling algorithm for periodic tasks with shared resources called SLPSR which ignores the system reliability. Secondly, we prove that the problem of the reliability-aware low power scheduling for periodic tasks with shared resources is NP-hard and present two heuristic algorithms called SPF and LPF respectively. Finally, we present a dynamic low power scheduling algorithm for periodic tasks with shared resources called DLPSR to reclaim the dynamic slack time to save energy while preserving the system reliability. Experimental results show that the presented algorithm can reduce the energy consumption while improving the system reliability. |
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