PERFORMABILITY ANALYSIS OF FORK-JOIN QUEUING-SYSTEMS

Fork-join queueing systems offer a natural modelling paradigm for para llel processing systems and for assembly operations in automated manuf acturing. The analysis of fork-join queueing systems has been an impor tant subject of research in recent years. Existing analysis methodolog ies-both exact and approximate-assume that the servers are failure-fre e. In this study, we consider fork-join queueing systems in the presen ce of server failures and compute the cumulative distribution of perfo rmability with respect to the response time of such systems. For this, we employ a computational methodology that uses a recent technique ba sed on randomization. We compare the performability of three different fork-join queueing models proposed in the literature: the distributed model, the centralized splitting model, and the split-merge model. Th e numerical results show that the centralized splitting model offers t he highest levels of performability, followed by the distributed split ting and split-merge models.