کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6874942 | 1441464 | 2018 | 45 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
SLA based healthcare big data analysis and computing in cloud network
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نظریه محاسباتی و ریاضیات
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
Large volume of multi-structured and low-latency patient data are generated in healthcare services, which is achallenging task to process and analyze within the Service Level Agreement (SLA). In this paper, a Parallel Semi-Naive Bayes (PSNB) based probabilistic method is used to process the healthcare big data in cloud for future health condition prediction. In order to improve the accuracy of PSNB method, a Modified Conjunctive Attribute (MCA) algorithm is proposed for reducing the dimension. Emergency condition of the patient is considered by setting a global priority among the patients and an Optimal Data Distribution (ODD) algorithm is proposed to position both batch and streaming patient data into the Spark nodes. Further, a Dynamic Job Scheduling (DJS) algorithm is designed to schedule the jobs efficiently to the most suitable nodes for processing the data taking SLA into account. Our proposed PSNB algorithm provides better accuracy of 87.8% for both batch and streaming data, which is 12.8% higher than the original Naive-Bayes (NB) algorithm and can conveniently be employed in various patient monitoring applications.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Parallel and Distributed Computing - Volume 119, September 2018, Pages 121-135
Journal: Journal of Parallel and Distributed Computing - Volume 119, September 2018, Pages 121-135
نویسندگان
Prasan Kumar Sahoo, Suvendu Kumar Mohapatra, Shih-Lin Wu,