Energy efficient scheduler of aperiodic jobs for real-time embedded systems
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Energy Efficient Scheduler of Aperiodic Jobs for Real-time Embedded Systems Hussein El Ghor1 1
E. M. Aggoune2
University Institute of Technology, Lebanese University, Lebanon Sensor Networks and Cellular Systems (SNCS) Research Center UT, Saudi Arabia 2
Electrical Engineering Department, University of Tabuk Sensor Networks and Cellular Systems (SNCS) Research Center 71491 Tabuk, Saudi Arabia
Abstract: Energy consumption has become a key metric for evaluating how good an embedded system is, alongside more performance metrics like respecting operation deadlines and speed of execution. Schedulability improvement is no longer the only metric by which optimality is judged. In fact, energy efficiency is becoming a preferred choice with a fundamental objective to optimize the system s lifetime. In this work, we propose an optimal energy efficient scheduling algorithm for aperiodic real-time jobs to reduce CPU energy consumption. Specifically, we apply the concept of real-time process scheduling to a dynamic voltage and frequency scaling (DVFS) technique. We address a variant of earliest deadline first (EDF) scheduling algorithm called energy saving-dynamic voltage and frequency scaling (ES-DVFS) algorithm that is suited to unpredictable future energy production and irregular job arrivals. We prove α , where S is the minimum speed of any job and C is the available energy that ES-DVFS cannot attain a total value greater than C/S capacity. We also investigate the implications of having in advance, information about the largest job size and the minimum speed used for the competitive factor of ES-DVFS. We show that such advance knowledge makes possible the design of semi-on-line algorithm, ES-DVFS∗∗ , that achieved a constant competitive factor of 0.5 which is proved as an optimal competitive factor. The experimental study demonstrates that substantial energy savings and highest percentage of feasible job sets can be obtained through our solution that combines EDF and DVFS optimally under the given aperiodic jobs and energy models. Keywords: systems.
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Real-time systems, energy efficiency, aperiodic jobs, scheduling, dynamic voltage scaling, low-power systems, embedded
Introduction
The number of embedded systems operated by batteries is constantly increasing with applications in autonomous robots, battlefields, industrial process monitoring, mobile communication systems, and environmental monitoring, to name but a few. In these systems, time is no longer the only metric by which performance is judged. In fact, reducing the energy consumption is of primary importance to prolong the battery life. Hence, the stringent timing constraints as well as reducing energy consumption are highly desirable and sometimes critical features of any embedded computing system. Due to increased computational demands, the obvious target for energy reduction became the processor. Recent reports show that the processor consumes more than 50% of the total energy[1] . Dynamic voltage and frequency scaling (DVFS) is a popular and widely used technique
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