EXPERIENTIAL LEARNING-BASED FEATURE INTERACTION DETECTION IN IMS

摘要：

The detection of feature interaction in IMS remains a challenging task. This paper investigates the feature interaction induced by multi-user and multi-service, analyses and describes them through formal language, and proposes an experiential learning-based detection algorithm. This algorithm regards the interaction occurring for the first time as an experience, which is self-learned from an actual conflict, when it recurs, the previous detection can provide some experience for the later detecting process, to predict interaction in advance. So the detection time can be advanced as well as the resolution time is reduced. Case study shows that this approach is effective and can detect the feature interaction much earlier than traditional methods.

关键词： IMS (IP Multimedia Subsystem) Feature Interaction.. Experiential Learning Predetection

作者: Jiuyun Xu Xiaoling Wei Cunqun Fan

作者单位: School of Computer and Communication Engineering,China University of Petroleum, Dongying, China Stat School of Computer and Communication Engineering,China University of Petroleum, Dongying, China School of Computer and Communication Engineering, China University of Petroleum, Dongying, China

会议类型: 国际会议

会议名称: 2010 3rd IEEE International Conference on Broadband Network & Multimedia Technology(2010年第三届IEEE宽带网络与多媒体国际会议 IC-BNMT 2010)

会议地点: 北京

会议语种:英文

页码: 823-827

在线出版日期: 2010-10-26（万方平台首次上网日期，不代表论文的发表时间）