A time series and reduction based model for QoS prediction of service ontologies

Yunni Xia, Jingjing Lv, Mengchu Zhou, Qingsheng Zhu, Xin Luo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

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.

Original languageEnglish (US)
Title of host publicationProceedings of the 11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014
PublisherIEEE Computer Society
Pages501-506
Number of pages6
ISBN (Print)9781479931064
DOIs
StatePublished - Jan 1 2014
Event11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014 - Miami, FL, United States
Duration: Apr 7 2014Apr 9 2014

Publication series

NameProceedings of the 11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014

Other

Other11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014
CountryUnited States
CityMiami, FL
Period4/7/144/9/14

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Control and Systems Engineering

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