Markov models are widely used for the analysis of availability of computer/communication systems. Realistic models often involve state space cardinalities that are so large that it is impractical to generate the transition rate matrix let alone solve for availability measures. Various state space reduction methods have been developed, particularly for transient analysis. In this paper we present an approximation technique for determining steady state availability. Of particular interest is that the method also provides bounds on the error. Examples are given to illustrate the method.

Markov models are widely used for the analysis of availability of computer/communication systems. Realistic models often involve state space card&&ties that are so large that it is impractical to generate the transition rate matrix let alone solve for availability measures. Various state space reduction methods have been developed, particularly for transient analysis. In this paper we present an approximation technique for determining steady state availability. Of particular interest is that the method also provides bounds on the error. Examples are given to illustrate the method.

This article reports about a study conducted to assess the quality of the top Brazilian Computer Science graduate programs. The study is based on data from DBLP and considers the scientific production of these programs in the triennial 2004--2006. A comparison of the scientific production of the Brazilian programs against that of reputable programs in North America and Europe indicates that the former compares well with these programs, both in terms of publication rate and number of graduates. The study also shows that the Brazilian programs follow international publication ratios of more than two conference papers per journal article. These results are a clear indication that the Computer Science field has reached maturity in Brazil.

Repairable computer systems are considered, the availability behavior of which can be modeled as a homogeneous Markov process. The randomization method is used to calculate various measures over a finite observation period related to availability modeling of these systems. These measures include the distribution of the number of events of a certain type, the distribution of the length of time in a set of states, and the probability of a near-coincident fault. The method is then extended to calculate performability distributions. The method relies on coloring subintervals of the finite observation period based on the particular application, and then calculating the measure of interest using these colored intervals.

No abstract