Back to University of Twente portal
Efficient heuristics for simulating rare events in queuing networks
Zaburnenko, Tatiana Sergeevna (2008) Efficient heuristics for simulating rare events in queuing networks. thesis.
![[img]](http://doc.utwente.nl/style/images/fileicons/application_pdf.png)
| PDF 1642Kb |
| Abstract: | In this thesis we propose state-dependent importance sampling heuristics to estimate the probability of population overflow in queuing networks. These heuristics capture state-dependence along the boundaries (when one or more queues are almost empty) which is crucial for the asymptotic efficiency of the change of measure. The approach does not require difficult (and often intractable) mathematical analysis or costly optimization involved in adaptive importance sampling methodologies. Experimental results on tandem, parallel, feed-forward, and a 2-node feedback Jackson queuing networks as well as a 2-node tandem non-Markovian network suggest that the proposed heuristics yield asymptotically efficient estimators, sometimes with bounded relative error. For these queuing networks no state-independent importance sampling techniques are known to be efficient. |
| Item Type: | Thesis |
| Faculty: | Electrical Engineering, Mathematics and Computer Science (EEMCS) |
| Research Group: | |
| Link to this item: | http://purl.utwente.nl/publications/58768 |
| Official URL: | http://dx.doi.org/10.3990/1.9789036526227 |
| Export this item as: | BibTeX EndNote HTML Citation Reference Manager |
Show download statistics for this publication
Show download statistics for this publicationRepository Staff Only: item control page
Metis ID: 251056