Self-healing in large-scale systems: parallel and distributed diagnostic architectures

Automated real-time problem diagnosis is a key feature of a self-healing system. However, rapidly growing size and complexity of modern distributed systems creates a challenge for traditional centralized diagnostic approaches and calls for parallel and distributed architectures. Dividing the system into subsystems controlled by separate diagnostic engines is an obvious choice; however, on top of that, a communication architecture must be provided that allows diagnostic engines to exchange information about common components in order to obtain better diagnosis. In this paper, we discuss a distributed belief propagation approach to diagnosis and provide a scalable parallel and distributed communication architecture that supports efficient message exchange among diagnostic engines.