Self-aware services: using Bayesian networks for detecting anomalies in Internet-based services

We propose a general architecture and implementation for the autonomous assessment of the health of arbitrary service elements, as a necessary prerequisite to self-control. We describe a health engine, the central component of our proposed `self-awareness and control´ architecture. The health engine combines domain independent statistical analysis and probabilistic reasoning technology (Bayesian networks) with domain dependent measurement collection and evaluation methods. The resultant probabilistic assessment enables open, non-hierarchical communications about service element health. We demonstrate the validity of our approach using HP´s corporate email service and detecting email anomalies: mail loops and a virus attack