Paper accepted at Sigmetrics’17

My paper Accelerating Performance Inference over Closed Systems by Asymptotic Methods has been accepted for presentation at ACM Sigmetrics’17 as a full paper!

The paper investigates the computation of likelihoods in closed multi-class queueing networks. Novel exact and asymptotic approximations for the normalizing constant of state probabilities are derived and shown to address computational limitations of prior art.