ISSN: 2182-2069 (printed) / ISSN: 2182-2077 (online)
Self-aware Services of NGSDP:Using Bayesian Networks for Measuring Quality of Convergent Services
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.