Performability analysis: measures, an algorithm, and a case study

Abstract

The behavior of the multiprocessor system is described as a continuous Markov chain, and a reward rate (performance measure) is associated with each state. The distribution of performability is evaluated for analytical models of a multiprocessor system using a polynomial-time algorithm that obtains the distribution of performability for repairable, as well as nonrepairable, systems with heterogeneous components with a substantial speedup over earlier work. Numerical results indicate that distributions of cumulative performance measures over finite intervals reveal behavior of multiprocessor systems not indicates by either steady-state or expected values alone.