Browsing by Author "Lin, Ming-Ham"

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Energy Efficient Intra-Task Dynamic Voltage Scaling for Realistic CPUs of Mobile Devices
(2009-01-01)
Yang, Chien-Chung
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Wang, Kuochen
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Lin, Ming-Ham
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Lin, Pochun
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資訊工程學系
It is not energy efficient to run a CPU at full speed all the time for all kinds of tasks in mobile devices. This paper proposes two energy efficient intra-task dynamic voltage scaling (DVS) algorithms for CPUs. There are three main contributions in this paper. Firstly, unlike the tedious derivation in PACE [2], we have derived the same optimal speed schedule with minimal energy consumption in a discrete and elegant way by using the Lagrange multiplier procedure. Secondly, the CPU model assumed in PACE is ideal, meaning that such a CPU supports all possible frequencies/voltage levels. We call such CPUs as ideal CPUs. In reality, CPUs only support a limited set of frequency/voltage levels, and we call this kind of CPUs as realistic CPUs. Thirdly, since energy consumption is not a simple function of frequency, it is more reasonable to transform the original nonlinear programming problem to the Multiple-Choice Knapsack Problem (MCKP). Since the problem can be described by a multistage graph, we used dynamic programming to derive an Optimal Schedule for Realistic CPUs (OSRC) with minimal energy consumption for realistic CPUs by using actual power consumption specifications of realistic CPUs. Considering potential computation and transition overheads, we have also proposed a low overhead OSRC (LO-OSRC), which restricts the change of CPU frequency/voltage to only once in the speed schedule. By using actual data from the power consumption specifications of two classical CPUs for evaluation, experimental results have shown that the energy saving of the proposed OSRC (LO-OSRC) is up to 10.3% (9.4%) better than that of PACE for realistic CPUs.
Energy efficient scheduling for real-time systems with mixed workload
(2007)
Chen, Jheng-Ming
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Wang, Kuochen
;
Lin, Ming-Ham
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資訊工程學系
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Department of Computer Science
In spite of numerous inter-task dynamic voltage scaling (DVS) algorithms of real-time systems with either periodic tasks or aperiodic tasks, few of them were aimed at the mixed workload of both kind of tasks. A DVS algorithm for mixed workload real-time systems should not only focus on energy saving, but also should consider low response time of aperiodic tasks. In this paper, we develop an on-line energy efficient scheduling, called Slack Stealing for DVS (SS-DVS), to reduce CPU energy consumption for mixed workload real-time systems under the earliest deadline first (EDF) scheduling policy. The SS-DVS is based on the concept of slack stealing to serve aperiodic tasks and to save energy by using the dynamic reclaiming algorithm (DRA). Unlike other existing approaches, the SS-DVS does not need to know the workload and the worst case execution time of aperiodic tasks in advance. Experimental results show that the proposed SS-DVS obtains better energy reduction (17% similar to 22%) while maintaining the same response time compared to existing approaches.