Evaluation of Internal Delay Inference in Queuing Networks
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Stoner, David E
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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.
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Keywords
Bivariate Markov chain, EM algorithm, Queuing network, Python