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Software Rejuvenation on a Grid Computing Environment for Higher Availability Based on Approximate Inverse Preconditioning

Grid computing is an innovative technology for using geographically distributed resources in order to solve large-scale problems providing heterogeneous resources. In this paper, a Grid computing environment with star topology is studied and in order to provide higher levels of Grid availability, a preventive software maintenance technique, called software rejuvenation, is proposed to be performed on certain Grid components. The aim of our work is to determine optimal rejuvenation policies that can provide higher levels of Grid asymptotic availability. Moreover, some indicators providing the level of contribution of each Grid component to system’s availability are defined and computed. Continuous Time Markov Chains (CTMC) are used in order to model the behavior of the studied Grid computing environment and explicit generalized approximate inverse preconditioning methods are used for solving efficiently sparse linear systems, in order to derive the asymptotic availability