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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. en_US
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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