کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6882707 | 1443883 | 2018 | 9 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Multi-level sample importance ranking based progressive transmission strategy for time series body sensor data
ترجمه فارسی عنوان
مقیاس درجه بندی چندمرحلهای براساس طبقهبندی مبتنی بر استراتژی انتقال پیشرفته برای دادههای سری حسگرهای بدن
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کلمات کلیدی
تحلیل داده ها، کیفیت خدمات، انتقال پیشرفته، داده های سری زمانی، شبکه های بدن منطقه،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
شبکه های کامپیوتری و ارتباطات
چکیده انگلیسی
Body sensors have gained increasing interest during the past several years. With more applications deployed, it is imperative to ensure the success of data analysis, which largely depends on data transmission reliability as well as the importance of samples received. Traditional approaches focus on improving data reliability through various schemes such as the prioritization of MAC access. However, in this paper we analyze the characteristics of time series body sensor data and propose to rank sample importance based on a multi-level approach. With this approach, samples are grouped into five levels, indicating their importance with regard to data analysis. Then, a progressive transmission strategy is designed to transmit samples in order of their importance so that the overall received data quality is maximized. Extensive experiment results indicate that as much as 40-60% bandwidth saving can be achieved while meeting the requirements of data analysis algorithms.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computer Networks - Volume 136, 8 May 2018, Pages 119-127
Journal: Computer Networks - Volume 136, 8 May 2018, Pages 119-127
نویسندگان
Ming Li, Joseph Reeves, Carlos Moreno,