  Many applications are implemented as multi-tier software systems, and are
executed on distributed infrastructures, like cloud infrastructures, to benefit
from the cost reduction that derives from dynamically allocating resources
on-demand. In these systems, failures are becoming the norm rather than the
exception, and predicting their occurrence, as well as locating the responsible
faults, are essential enablers of preventive and corrective actions that can
mitigate the impact of failures, and significantly improve the dependability of
the systems. Current failure prediction approaches suffer either from false
positives or limited accuracy, and do not produce enough information to
effectively locate the responsible faults. In this paper, we present PreMiSE, a
lightweight and precise approach to predict failures and locate the
corresponding faults in multi-tier distributed systems. PreMiSE blends
anomaly-based and signature-based techniques to identify multi-tier failures
that impact on performance indicators, with high precision and low false
positive rate. The experimental results that we obtained on a Cloud-based IP
Multimedia Subsystem indicate that PreMiSE can indeed predict and locate
possible failure occurrences with high precision and low overhead.
