DocumentCode
142631
Title
A time series and reduction based model for QoS prediction of service ontologies
Author
Yunni Xia ; Jingjing Lv ; Mengchu Zhou ; Qingsheng Zhu ; Xin Luo
Author_Institution
Software Theor. & Technol. Chongqing Key Lab., Chongqing Univ., Chongqing, China
fYear
2014
fDate
7-9 April 2014
Firstpage
501
Lastpage
506
Abstract
In this study, we introduce a dynamic framework to predict the runtime QoS of OWL-S ontologoies by employing an Autoregressive-Moving-Average Model and QoS reduction rules. In the case study of a real-world ontology sample, a comparison between existing approaches and the proposed one is presented and results suggest that the proposed one achieves higher prediction accuracy.
Keywords
autoregressive moving average processes; ontologies (artificial intelligence); semantic Web; time series; OWL-S ontologies; QoS prediction; QoS reduction rules; autoregressive-moving-average model; quality of service; reduction based model; service ontologies; time series; Abstracts; Ontologies; Quality of service; Reliability; Tiles;
fLanguage
English
Publisher
ieee
Conference_Titel
Networking, Sensing and Control (ICNSC), 2014 IEEE 11th International Conference on
Conference_Location
Miami, FL
Type
conf
DOI
10.1109/ICNSC.2014.6819677
Filename
6819677
Link To Document