Volume 1 - Issue 1
Self-aware Services of NGSDP:Using Bayesian Networks for Measuring Quality of Convergent Services
- Zhi Luo
School of Software Engineering Beijing University of Posts and Telecommunications Beijing, China
luozhi1989@gmail.com
- Junping Wang
School of Software Engineering Beijing University of Posts and Telecommunications Beijing, China
wangjunping@bupt.edu.cn
- Qiliang Zhu
School of Software Engineering Beijing University of Posts and Telecommunications Beijing, China
zhuqiliang@buptnet.edu.com
Keywords: Self-aware, convergent services, NGSDP, MMS.
Abstract
We propose a general architecture and implementation for the autonomous assessment of quality
of arbitrary service elements in the convergent service environments. We describe a quality engine,
which is the central component of our proposed architecture of self-aware convergent services of
NGSDP. The quality engine combines domain independent statistical analysis and probabilistic rea-
soning technology (Bayesian networks) with domain dependent measurement collection and evalu-
ation methods. The resultant probabilistic assessment can be transported via network protocols in
the convergent services and it enables non-hierarchical communications about the quality of service
elements. We demonstrate the validity of our approach using Multimedia Messaging Service (MMS)
Relay/Server and detecting anomalies: storage overflow and message expiration.