A Framework for Automated Fault Recovery Planning in Large-Scale Virtualized Infrastructures

Multi-layered provisioning architectures such as those in emergent virtualized (e.g. cloud) infrastructures exacerbate the cost of faults to a degree where automation effectively constitutes a prerequisite for operations. The acquisition of management information and the execution of routine tasks have been automated to some degree; however the decision processes behind fault management in large-scale environments have not. This paper addresses automation of such decision processes by proposing a planning-based fault recovery algorithm based on hierarchical task networks and data models for the knowledge necessary to the recovery process. We embed these concepts in a generic architecture and evaluate its prototypical implementation with respect to function and scalability.