Bayesian approach for Join-the-Shortest-Queue Model

par Yiqiang Q. Zhao (Carleton University, Ottawa)

vendredi 7 déc. 2018, 10:30 → 11:30 Europe/Paris

Salle E2 1180 (Tours)

In this talk, we describe challenges in modeling and analyzing queueing systems with incomplete information, which is often the case arising from large-scaled systems with dependence such as various Internet applications involving big data.  In such situations, it can be too cost to collect all necessary data (say missing data), required for statistical inference; or such data may not be available (say with delayed information).  In this talk, we first start with a simple example to demonstrate basic ideas and concepts; and then show how Bayesian approach works for the join-the-shortest-queue (JSQ for short) model with two parallel queues, where the servers may be heterogeneous.  Specifically, we show how a Bayesian approach can be applied to estimate unknown system parameters and to how the prediction on certain stationary metric can be made the JSQ model. Finally, we propose some ideas to deal with the model with either missing information or with delayed information.

This talk is based on the joint work with Ehssan Ghashim.