The Impact Failure Detector

Anubis G. M. Rossetto, Cláudio F. R. Geyer, Luciana Arantes, Pierre Sens

This work proposes a new and flexible unreliable failure detector whose output is related to the trust level of a set of processes. By expressing the relevance of each process of the set by an impact factor value, our approach allows the tuning of the detector output, making possible a softer or stricter monitoring. The idea behind our proposal is that, according to an acceptable margin of failures and the impact factor assigned to processes, in some scenarios, the failure of some low impact processes may not change the user confidence in the set of processes, while the crash of a high impact factor process may seriously affect it. We outline the application scenarios and the proposed unreliable failure detector, giving a detailed account of the concept on which it is based.

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