کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6888689 1445075 2017 26 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Energy consumption of data mining algorithms on mobile phones: Evaluation and prediction
ترجمه فارسی عنوان
مصرف انرژی الگوریتم های داده کاوی بر روی تلفن های همراه: ارزیابی و پیش بینی
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر شبکه های کامپیوتری و ارتباطات
چکیده انگلیسی
The pervasive availability of increasingly powerful mobile computing devices like PDAs, smartphones and wearable sensors, is widening their use in complex applications such as collaborative analysis, information sharing, and data mining in a mobile context. Energy characterization plays a critical role in determining the requirements of data-intensive applications that can be efficiently executed over mobile devices. This paper presents an experimental study of the energy consumption behavior of representative data mining algorithms running on mobile devices. Our study reveals that, although data mining algorithms are compute- and memory-intensive, by appropriate tuning of a few parameters associated to data (e.g., data set size, number of attributes, size of produced results) those algorithms can be efficiently executed on mobile devices by saving energy and, thus, prolonging devices lifetime. Based on the outcome of this study we also proposed a machine learning approach to predict energy consumption of mobile data-intensive algorithms. Results show that a considerable accuracy is achieved when the predictor is trained with specific-algorithm features.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pervasive and Mobile Computing - Volume 42, December 2017, Pages 248-264
نویسندگان
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