Performability Analysis: Measures, an Algorithm, and a Case Study

Multiprocessor systems can provide higher performance and higher reliability/availability than single-processor systems. In order to properly assess the effectiveness of multiprocessor systems, measures that combine performance and reliability are needed. We describe the behavior of the multiprocessor system as a continuous-time Markov chain and associate a reward rate (performance measure) with each state. We evaluate the distribution of performability for analytical models of a multiprocessor system using a new 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 indicated by either steady-state or expected values alone. © 1988 IEEE

Duke Scholars

Author Kishor S. Trivedi Electrical and Computer Engineering