Robust and Adaptive Modeling of Software Aging

1. Introduction The widespread phenomenon of software (image) aging is known to cause performance degradation, transient failures or even crashes of applications. This undesired behavior is especially visible in long-running software such as web and application servers and enterprise always-on applications-software deployed frequently in Grid and utility computing environments. The management costs caused by this problem are considerable as the root causes cannot be usually fixed due to unavailability of the source code, and since simple replication schemata do not work efficiently. The primary method to fight aging is software rejuvenation, i.e. a restart of the aging application periodically or adaptively. The latter approach takes into account the progress of aging and the effects of transient errors in order to find rejuvenation schedules which maximize the overall application availability and performance [3]. It has obvious advantages over the periodical rejuvenation schema yet it requires aging models which are able to predict the expected performance at least over a part of the rejuvenation cycle. There are two basic approaches to apply proactive software rejuvenation: (i) Analytic-based approach; (ii) Measurement-based approach. The first approach uses analytic modeling of a system, assuming some distributions for