Adaptive software rejuvenation: degradation model and rejuvenation scheme

Abstract

We present a framework of adaptive estimation and rejuvenation of software system performance in the presence of aging sources. The framework specifies that a degradation model not only describe an aging process but also enable the adaptation of model-based performance estimates to on-line measurements of data pertaining to the aging process. The adaptive estimation uses model-based a priori estimation and obtains a posteriori estimation based on the data measurements. With the adaptive estimation, the rejuvenation policy determines the time epochs for data collection and rejuvenation according to system dynamics. In the specific context of resource leaks previously assumed to lead to aging, we present a non-homogeneous Markov model to explicitly establish a connection between resource leaks and the failure rate. We demonstrate an increasing failure rate in the presence of resource leaks. 1. Introduction: the Adaptation Problem We present a framework for adaptive estimation and rejuvenation of software system performance in the presence of aging sources. We are concerned with system resource loss, in particular, memory leakage. Memory is indispensable in computer and communication systems. Memory leakage is a typical aging source for server systems due to software bugs in the client applications that use server resources. Our framework for adaptive estimation and rejuvenation consists of three integral components: a degradation model, an adaptive estimation scheme, and an adaptive rejuvenation scheduling policy. The degradation model allows adaptation of model-based performance estimates to on-line measurements of data pertaining to the aging process. The adaptive estimation scheme uses the model-based a priori estimation and obtains a posteriori estimation based on the measurements. With the adaptive estimation, the rejuvenation scheduling policy determines time epochs for data