Stochastic performability measurement for software system with random performance degradation and field-oriented restoration

Abstract

This paper constructs the integrated software performability model reflecting the actual field environment. The time-dependent behavior of the system alternating between up and down states is described by the Markov process. Then we incorporate the undesirable operational state and the field-oriented restoration scenario into the model, i.e., we consider the following two types of operational state: one is operating with the desirable performance level according to specification and the other is with degraded performance level, and the following two types of restoration: one is the restoration with debugging and the other is without debugging. Assuming that the software system can process the multiple tasks simultaneously, we describe the arrival process of the tasks follows a nonhomogeneous Poisson process and treat the processing time limit imposed on each task as a random variable. We analyze the distribution of the number of tasks whose processes can be completed within the processing time limit with the infinite server queueing model. From the model, we derive several software performability measures considering the real-time property. Finally, we illustrate several numerical examples of the measures to investigate the impacts of the difference of the operational performance levels and the field-oriented restoration on the system performability evaluation.