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Evaluation of Internal Delay Inference in Queuing Networks

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dc.contributor.advisor Mark, Brian L Stoner, David E
dc.creator Stoner, David E 2016-04-29 2016-10-09T14:46:53Z 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.language.iso en en_US
dc.subject Bivariate Markov chain en_US
dc.subject EM algorithm en_US
dc.subject queuing network en_US
dc.subject Python en_US
dc.title Evaluation of Internal Delay Inference in Queuing Networks en_US
dc.type Thesis en_US Master of Science in Electrical Engineering en_US Master's en_US Electrical Engineering en_US George Mason University en_US

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