An architecture for online-diagnosis systems supporting compressed communication

With its ability to detect, identify and, if applicable, recover from occurred faults, online-diagnosis can help achieving fault-tolerant systems. A sound decision on an occurred fault is the foundation for fault-specific recovery actions. For this, typically a large amount of data has to be analyzed and evaluated. A diagnostic process implemented on a distributed system needs to communicate all those data among the network which is an expensive affair in terms of communication resources and time. In this paper we present an architecture for a distributed online-diagnosis system with real time constraints that supports data compression to reduce the communication time. We further present a library of lossy compression methods with guaranteed compression ratios that are suitable for real time purposes.