Multi-perspective evaluation of self-healing systems using simple probabilistic models

Rean Griffith, Gail E. Kaiser, Javier Alonso López

Abstract: In this paper we construct an evaluation framework for a self-healing system, VM-Rejuv -- a virtual machine based rejuvenation scheme for web-application servers -- using simple, yet powerful, probabilistic models that capture the behavior of its self-healing mechanisms from multiple perspectives (designer, operator, and end-user). We combine these analytical models with runtime fault-injection to study the operation of VM-Rejuv, and use the results from the fault-injection experiments and model-analysis to reason about the efficacy of VM-Rejuv, its limitations and strategies for mitigating these limitations in system-deployments. Whereas we use VM-Rejuv as the subject of our evaluation in this paper, our main contribution is the demonstration of a practical evaluation approach that can be generalized to other self-healing systems.