Evaluation of Internal Delay Inference in Queuing Networks
| dc.contributor.advisor | Mark, Brian L | |
| dc.contributor.author | Stoner, David E | |
| dc.creator | Stoner, David E | |
| dc.date | 2016-04-29 | |
| dc.date.accessioned | 2016-10-09T14:46:53Z | |
| dc.date.available | 2016-10-09T14:46:53Z | |
| dc.description.abstract | Statistical inference of internal computer network characteristics using only externally made measurements is extremely useful in the analysis of highly complex networks. This the- sis seeks to implement and test an expectation-maximization (EM) algorithm that uses these observations to estimate total end-to-end network delay density, link delay density and prob- ability of route selection. The EM algorithm in question was tested using source/destination delays generated from a custom queuing network simulator. The parameters of the queuing network were varied in order to determine the e ectiveness of the algorithm on Jackson-type networks as well as more realistic networks. The subsequent results of the algorithm are compared against the actual network simulation data to evaluate the performance of the algorithm. | |
| dc.identifier.uri | https://hdl.handle.net/1920/10487 | |
| dc.language.iso | en | |
| dc.subject | Bivariate Markov chain | |
| dc.subject | EM algorithm | |
| dc.subject | Queuing network | |
| dc.subject | Python | |
| dc.title | Evaluation of Internal Delay Inference in Queuing Networks | |
| dc.type | Thesis | |
| thesis.degree.discipline | Electrical Engineering | |
| thesis.degree.grantor | George Mason University | |
| thesis.degree.level | Master's | |
| thesis.degree.name | Master of Science in Electrical Engineering |