Failure prediction for autonomic management of networked computer systems with availability assurance

Networked computer systems continue to grow in scale and in the complexity of their components and interactions. Component failures become norms instead of exceptions in these environments. Failure occurrence as well as its impact on system performance and operation costs are becoming an increasingly important concern to system designers and administrators. To achieve self-management of failures and resources in networked computer systems, we propose a framework for autonomic failure management with hierarchical failure prediction functionality for large coalition systems, such as coalition clusters and compute grids. It analyzes node, cluster and system wide failure behaviors and forecasts the prospective failure occurrences based on quantified failure dynamics. Failure correlations are inspected by the predictor. Experimental results in a computational grid on campus show the offline and online predictions by our predictors accurately forecast the failure trend and capture failure correlations in the production environment.