Proactive Personalized Services in Large-Scale IoT-Based Healthcare Application

被引:1
作者
He, Shuqing [1 ]
Cheng, Bo [1 ]
Huang, Yuze [1 ]
Duan, Li [1 ]
Chen, Junliang [1 ]
机构
[1] Beijing Univ Posts & Telecommun, State Key Lab Networking & Switching Technol, Beijing, Peoples R China
来源
2017 IEEE 24TH INTERNATIONAL CONFERENCE ON WEB SERVICES (ICWS 2017) | 2017年
关键词
complex event pattern; personalized services; partitioning; clustering; IoT-Based Healthcare Application; INTERNET; THINGS;
D O I
10.1109/ICWS.2017.96
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
With the IoT technology increasing and aging social have coming, personalized service assisted elder and patient living is a critical application in IoT-Based Healthcare application. However, the scale and complexity of personalized service is increasing with wildly applied to our life, which cause response time increase and resource waste in large-scale IoT-Based Healthcare application. Therefore, it is necessary of studying on dealing with the large-scale and complexity of personalized services in large-scale IoT-Based Healthcare application. In this paper, we propose proactive personalized service leveraging Complex Event Processing ( CEP) to deal with a large number and complexity of personalized services. Firstly, personalized service defined as complex event pattern that expresses in the form of Directed Acyclic Graph ( DAG). Secondly, we propose a complex event pattern partitioning and clustering algorithms to optimize the processing of dealing with personalized services. Finally, we realize a prototype system based on proposed approach named BCEPCare. Experiment result shows that BCEPCare is superior to the traditional ESPER in large-scale IoT-Based healthcare application.
引用
收藏
页码:808 / 813
页数:6
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