Details

Autor(en) / Beteiligte

• Ross, Keith W
• Tsang, Danny H K
• Wang, Jie

Titel

Monte Carlo summation and integration applied to multiclass queuing networks

Ist Teil von

• Journal of the ACM, 1994-11, Vol.41 (6), p.1110-1135

Ort / Verlag

New York: Association for Computing Machinery

Erscheinungsjahr

1994

Quelle

ACM Digital Library

Beschreibungen/Notizen

• Although many closed multiclass queuing networks have a product-form solution, evaluating their performance measures remains nontrivial due to the presence of a normalization constant. We propose the application of Monte Carlo summation in order to determine the normalization constant, throughputs, and gradients of throughputs. A class of importance-sampling functions leads to a decomposition approach, where separate single-class problems are first solved in a setup module, and then the original problem is solved by aggregating the single-class solutions in an execution model. We also consider Monte Carlo methods for evaluating performance measures based on integral representations of the normalization constant; a theory for optimal importance sampling is developed. Computational examples are given that illustrate that the Monte Carlo methods are robust over a wide range of networks and can rapidly solve networks that cannot be handled by the techniques in the existing literature.