Performability Analysis Using Semi-Markov Reard Processes

Performability Analysis Us ing Semi-Markov Reward Processes

With the increasing complexity of multiprocessor and distributed processing systems, the need to develop efficient and accurate modeling methods is evident. Fault tolerance and degradable performance of such systems has given rise to considerable interest in models for the combined evaluation of performance and reliability [l], [2]. Markov or semi-Markov reward models can be used to evaluate th...

Performability Optimization using Linear Bounds of Partially Observable Markov Decision Processes

Markov Decision Processes (MDPs) and Partially Observable MDPs (POMDPs) have been proposed as a framework for performability management. However, exact solution of even small POMDPs is very difficult because of their potentially infinite induced state spaces. In this paper, we present new lower bounds on the accumulated reward measure for MDPs and POMDPs. We describe how the bounds can be used ...

The KTH Visit in Semi-Markov Processes

Multiprocessor Performability Analysis

Conclusions Performability models of multiprocessor systems and their evaluation are presented. Two cases in which hierarchical modeling is applied are examined. 1. Models are developed to analyze the behavior of processor arrays of various sizes in the presence of permanent, transient, intermittent, and near-coincident faults. Models can be generated for typical reconfiguration schemes that co...

Approximate Performability and Dependability Analysis Using Generalized Stochastic Petri Nets

Haverkort, B.R., Approximate performability and dependability analysis using generalized stochastic Petri nets, Performance Evaluation 18 (1993) 61-78. Since current day fault-tolerant and distributed computer and communicat ion systems tend to be large and complex, their corresponding performability models will suffer from the same characteristics. Therefore, calculating performability measure...