To resolve the matters of poor self-adapting ability and low accessing efficiency of data service systems for college student mental health education, a universal plug and play (UPnP) based cloud framework and self-adapting service methods were proposed. A cloud framework model for college student mental health was set up, and the dynamical response for network architecture (NA) was performed. A data collecting algorithm with monitoring and scheduling was put forward to realize playback and comparative analysis for different users, time and conditions. A mental health cloud service system was developed, and the technical index and ergonomic performance comparative experiments with the C/S-based systems were performed. The comparative results showed that the access accuracy of data transaction process was improved 80%, the average query time was decreased 68%, the wrong processing probability per 1000 data records was decreased 84%, the off-line-interrupt probability per 1000 sessions was decreased 82%, the data package loss probability for data query process was decreased 91%, the general satisfy degree was increase 28%, the instance analysis efficiency per working day was improved 27, and the parallel users could increase 5 times of C/S systems. The college student mental health cloud service system runs stably, inquires quickly, has perfect exception mechanism, and can provide mobile on-line data service for college student mental health education.
Chen Shuting
,
Zhou Wenxia
,
Wang Jue
,
Wang Jiajun
. Cloud framework and self-adapting service methods for college student mental health education[J]. Chinese Journal of Medical Education, 2017
, 37(6)
: 896
-903
.
DOI: 10.3760/cma.j.issn.1673-677X.2017.06.021
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