Article ID: | iaor19961598 |
Country: | United Kingdom |
Volume: | 46 |
Issue: | 10 |
Start Page Number: | 1237 |
End Page Number: | 1249 |
Publication Date: | Oct 1995 |
Journal: | Journal of the Operational Research Society |
Authors: | Narahari Y., Sundarrajan P. |
Keywords: | production |
Fork-join queueing systems offer a natural modelling paradigm for parallel processing systems and for assembly operations in automated manufacturing. The analysis of fork-join queueing systems has been an important subject of research in recent years. Existing analysis methodologies-both exact and approximate-assume that the servers are failure-free. This study considers fork-join queueing systems in the presence of server failures and computes the cumulative distribution of performability with respect to the response time of such systems. For this, the study employs a computational methodology that uses a recent technique based on randomization. It compares 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. The numerical results show that the centralized splitting model offers the highest levels of performability, of three different fork-join queueing models proposed in the literature: the distributed model, the centralized splitting model, and the split-merge model. The numerical results show that the centralized splitting model offers the highest levels of performability, followed by the distributed splitting and split-merge models.