Name
Abstract | ||
|---|---|---|
Queuing systems of any domain oftentimes exhibit correlated arrivals that considerably influence system behavior. Unfortunately, the vast majority of simulation modeling applications and programming languages do not provide the means to properly model the corresponding input processes. In order to obtain valid models, there is a substantial need for tools capable of modeling autocorrelated input processes. Accordingly, this paper provides a review of available tools to fit and model these processes. In addition to a brief theoretical discussion of the approaches, we provide tool evaluation from a practitioners perspective. The assessment of the tools is based on their ability to model input processes that are either fitted to a trace or defined explicitly by their characteristics, i.e., the marginal distribution and autocorrelation coefficients. In our experiments we found that tools relying on autoregressive models performed the best. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/WSC.2016.7822164 | Winter Simulation Conference |
Field | DocType | ISSN |
Time series,Autoregressive model,Simulation,Computer science,Simulation modeling,Context model,Queueing theory,Marginal distribution,Autocorrelation | Conference | 0891-7736 |
ISBN | Citations | PageRank |
978-1-5090-4484-9 | 1 | 0.35 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tobias Uhlig | 1 | 5 | 5.20 |
| Oliver Rose | 2 | 17 | 10.43 |
| Sebastian Rank | 3 | 2 | 1.70 |