Power analysis of embedded operating systems

Dick, Robert P.; Lakshminarayana, G.; Raghunathan, Anand; Jha, Niraj K.

doi:10.1145/337292.337427

Cited by 70 publications

(47 citation statements)

References 12 publications

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“…6 and 7, which show the energy overhead one pays for an RTOS. This closely mirrors the overhead one pays in terms of execution time as well [10]. Results are only shown for the applications with the least (IPC) and greatest (FIR) overhead per job invocation.…”

Section: Energy Consumptionmentioning

confidence: 69%

“…High-level language modeling of applications and their operating systems has been performed by the SimOS group [34] and there has been a large number of recent studies modeling the power consumption of microprocessors and applications [22], [19], [20], [14], [7], [43], [38], [39], [31], [32], [13], but ours is one of the few experimental environments that performs both (the only other one of which we are aware is described in [10]). …”

Section: Motivationmentioning

confidence: 99%

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The performance and energy consumption of embedded real-time operating systems

Baynes

Collins

Fiterman³

et al. 2003

IEEE Trans. Comput.

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Abstract-This paper presents the modeling of embedded systems with SimBed, an execution-driven simulation testbed that measures the execution behavior and power consumption of embedded applications and RTOSs by executing them on an accurate architectural model of a microcontroller with simulated real-time stimuli. We briefly describe the simulation environment and present a study that compares three RTOSs: C/OS-II, a popular public-domain embedded real-time operating system; Echidna, a sophisticated, industrial-strength (commercial) RTOS; and NOS, a bare-bones multirate task scheduler reminiscent of typical "roll-your-own" RTOSs found in many commercial embedded systems. The microcontroller simulated in this study is the Motorola M-CORE processor: a low-power, 32-bit CPU core with 16-bit instructions, running at 20MHz. Our simulations show what happens when RTOSs are pushed beyond their limits and they depict situations in which unexpected interrupts or unaccounted-for task invocations disrupt timing, even when the CPU is lightly loaded. In general, there appears no clear winner in timing accuracy between preemptive systems and cooperative systems. The power-consumption measurements show that RTOS overhead is a factor of two to four higher than it needs to be, compared to the energy consumption of the minimal scheduler. In addition, poorly designed idle loops can cause the system to double its energy consumption-energy that could be saved by a simple hardware sleep mechanism.

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Section: Energy Consumptionmentioning

confidence: 69%

Section: Motivationmentioning

confidence: 99%

The performance and energy consumption of embedded real-time operating systems

Baynes

Collins

Fiterman³

et al. 2003

IEEE Trans. Comput.

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show abstract

“…Also, the authors do not consider the I/O drivers in the proposed energy consumption model. Dick et al [5] analyzed the power consumption of the μCOS OS which is running several embedded applications on a Fujitsi SPARClite processor based embedded system. The authors demonstrated that the OS functions have an important impact on the total energy consumption.…”

Section: Related Workmentioning

confidence: 99%

Accurate energy characterization of OS services in embedded systems

Ouni

Belleudy

Senn³

2012

J Embedded Systems

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As technology scales for increased circuit density and performance, the management of power consumption in embedded systems is becoming critical. Because the operating system (OS) is a basic component of the embedded system, the reduction and characterization of its energy consumption is a main challenge for the designers. In this work, a flow of low power OS energy characterization is introduced. The variation of the energy and power consumption of the embedded OS services is studied. The remainder of this article details the methods used to determine energy and power overheads of a set of basic services of the embedded OS: scheduling, context switch and inter-process communication. The impacts of hardware and software parameters like processor frequency and scheduling policy on the energy consumption are analyzed. Also, models and laws of the power and energy are extracted. Then, to quantify the low power OS energetic overhead, the obtained models are integrated in the system level design. Our method allows estimating the energy consumption of the low power OS services when running an application on a specific hardware platform.

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“…Indeed, researchers in the past have focused mainly on the performance of RTOSes [19] [17]. The first attempt to assess the energy overhead of an embedded OS is reported in [6]. This work analyses the power profile of a commercial RTOS by running two applications and evaluating the power consumed by the operating system calls.…”

Section: Related Workmentioning

confidence: 99%