T6/1 Performance Analysis of Queueing Networks with Blocking Simonetta Balsamo Dipartimento di Informatica, Università Ca’ Foscari di Venezia, Venice, Italy {balsamo@dsi.unive.it} Abstract Queueing network models have been widely applied for performance modeling and analysis of computer networks. Queueing network models with finite capacity queues and blocking (QNB) allow representing and analyzing systems with finite resources and population constraints. Different protocols can be defined to deal with finite capacity resources and they can be modeled in queueing networks with blocking by various blocking types or mechanisms. Modeling heterogeneous networks having different blocking protocols leads to heterogeneous QNB where the service centers may have different blocking types. QNB are difficult to analyze, except for the special class of product-form networks. Most of the analytical methods proposed in literature provide an approximate solution with a limited computational cost. This tutorial introduces queueing network models with finite capacity queues and various types of blocking. We discuss the main solution techniques for their exact and approximate analysis to derive network performance indices. We present and compare the solution methods for open and closed networks to identify the criteria for the appropriate selection of a solution method. We provide some application examples of this class of models to computer and communication networks. 1. Introduction Queueing network models have been widely applied for performance modeling, analysis and prediction of various systems, including communication and computer networks. They allow representing resource contention by a set of customers. The servers of the queueing network represent the resources and the customers that queue to obtain service represents the jobs, tasks, packets or messages that are the system workload. System performance analysis based on queueing networks consists of the evaluation of a set of figures of merit such as some average performance indices that include system throughput, resource utilization, customer’s mean response time or delay. The analysis of queueing networks is usually based on the definition of the underlying stochastic process, specifically a continuous time Markov chain. Some efficient solution algorithms have been defined for the special class of product-form queueing networks [Kl76, Ka92, L83, T01, BCMP75]. Some important characteristics of resource sharing systems such as computer and communication networks that affect system performance are the finite buffer space of the queues and possible constraints on the number of customers in the network or in a subnetwork. Queueing network models with finite capacity queues and blocking (QNB) allow representing and analyzing systems with finite resources and population constraints [BDO01, P94]. Different protocols can be defined to deal with finite capacity resources and they can be modeled in queueing networks with blocking by various blocking types or mechanisms. Modeling heterogeneous networks having different blocking protocols leads to heterogeneous QNB where the service centers may have different blocking types.