Deterministic Models of Software Aging and Optimal Rejuvenation Schedules

Automated modeling of software aging processes is a prerequisite for cost-effective usage of adaptive software rejuvenation as a self-healing technique. We consider the problem of such automated modeling in server-type applications whose performance degrades depending on the "work" done since last rejuvenation, for example the number of served requests. This type of performance degradation - caused mostly by resource depletion - is common, as we illustrate in a study of the popular Axis Soap server 1.3. In particular, we propose deterministic models for approximating the leading indicators of aging and an automated procedure for statistical testing of their correctness. We further demonstrate how to use these models for finding optimal rejuvenation schedules under utility functions. Our focus is on the important case that the utility function is the average of a performance metric (such as maximum service rate). We also consider optional SLA constraints under which the performance should never drop below a specified level. Our approach is verified by a study of the aging processes in the Axis Soap 1.3 server. The experiments show that the deterministic modeling technique is appropriate in this case, and that the optimization of rejuvenation schedules can greatly improve the average maximum service rate of an aging application.