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TEEC: Improving power consumption estimation of software

Abstract : Recently, researchers have begun to give importance at the energy consumed by software. But, to solve this problem, they propose often a hardware study of different devices. For this, they used hardware devices like powermeter or printed circuit. The main advantage of this methodology is the fact that we can obtain accurate results because we measure the energy consumed by components. But, we are limited at the fact that we can’t measure the power consumed by VM (Virtual Machine) and the cost of this process itself can be expansive. Estimating power consumption of software has begun a popular research field. Several tools have been presented in academic literature, however, these tools have the capacity to estimate only specific component’s consumption.ICT (Information and Communications Technologies) constitutes 2% of such gas emissions, and it is projected an increase to 4% by 2020, if nothing is done [1]. In fact, recent trends such as cloud computing and internet of things even increase the number of devices, and consequently the software running on them. Hence, software became a fundamental actor of efficiency plans that aims at reducing greenhouse gas emission.In this paper, we propose a tool, called TEEC (Tool to Estimate Energy Consumption), in order to estimate the power consumption of a given software at runtime by taking into account CPU, memory and disk power consumptions. Using TEEC, we expect to be able to obtain software/applications having some functionality and consuming less power.
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Submitted on : Monday, March 27, 2017 - 12:46:12 PM
Last modification on : Saturday, September 11, 2021 - 3:18:28 AM
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  • HAL Id : hal-01496262, version 1


Hayri Acar, Gülfem Alptekin, Jean-Patrick Gelas, Parisa Ghodous. TEEC: Improving power consumption estimation of software. EnviroInfo 2016, Sep 2016, Berlin, Germany. pp.335-341 / ISBN 978-3-8440-4687-8. ⟨hal-01496262⟩



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