GreenOracle: Estimating Software Energy Consumption with Energy Measurement Corpora

S. Chowdhury, Abram Hindle
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引用次数: 52

Abstract

Software energy consumption is a relatively new concern for mobile application developers. Poor energy performance can harm adoption and sales of applications. Unfortunately for the developers, the measurement of software energy con-sumption is expensive in terms of hardware and difficult in terms of expertise. Many prior models of software energy consumption assume that developers can use hardware instrumentation and thus cannot evaluate software runningwithin emulators or virtual machines. Some prior modelsrequire actual energy measurements from the previous versions of applications in order to model the energy consumption of later versions of the same application.In this paper, we take a big-data approach to software energy consumption and present a model that can estimate software energy consumption mostly within 10% error (in joules) and does not require the developer to train on energy measurements of their own applications. This model leverages a big-data approach whereby a collection of prior applications’ energy measurements allows us to train, trans-mit, and apply the model to estimate any foreign application’s energy consumption for a test run. Our model is based on the dynamic traces of system calls and CPU utilization.
GreenOracle:利用能量测量语料库估算软件能耗
对于移动应用程序开发人员来说,软件能耗是一个相对较新的问题。较差的能源性能会影响应用程序的采用和销售。不幸的是,对于开发人员来说,软件能耗的度量在硬件方面是昂贵的,而在专业知识方面是困难的。许多先前的软件能耗模型假设开发人员可以使用硬件工具,因此无法评估在模拟器或虚拟机中运行的软件。一些先前的模型需要从先前版本的应用程序中实际测量能量,以便对同一应用程序的后续版本的能量消耗进行建模。在本文中,我们采用大数据方法来计算软件能耗,并提出了一个模型,该模型可以估计软件能耗,误差在10%以内(以焦耳为单位),并且不需要开发人员对他们自己的应用进行能量测量培训。该模型利用了一种大数据方法,通过收集以前应用程序的能量测量数据,我们可以训练、传输和应用该模型来估计任何国外应用程序的测试运行能耗。我们的模型基于系统调用和CPU利用率的动态跟踪。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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