The Queueing Network Analyzer

TLDR

Packet‑switched communication networks require congestion models that capture bursty traffic and nearly constant packet service times. This paper presents QNA, a Bell Labs software package that estimates congestion in queueing networks while addressing non‑Poisson arrivals and non‑exponential service times. QNA’s first version analyzes open, FCFS multiserver networks without capacity limits by approximating arrivals and services with two or three parameters, treating each node as a GI/G/m queue, and aggregating network congestion under an independence assumption.

Abstract

This paper describes the Queueing Network Analyzer (QNA), a software package developed at Bell Laboratories to calculate approximate congestion measures for a network of queues. The first version of QNA analyzes open networks of multiserver nodes with the first-come, first-served discipline and no capacity constraints. An important feature is that the external arrival processes need not be Poisson and the service-time distributions need not be exponential. Treating other kinds of variability is important. For example, with packet-switched communication networks we need to describe the congestion resulting from bursty traffic and the nearly constant service times of packets. The general approach in QNA is to approximately characterize the arrival processes by two or three parameters and then analyze the individual nodes separately. The first version of QNA uses two parameters to characterize the arrival processes and service times, one to describe the rate and the other to describe the variability. The nodes are then analyzed as standard GI/G/m queues partially characterized by the first two moments of the interarrival-time and service-time distributions. Congestion measures for the network as a whole are obtained by assuming as an approximation that the nodes are stochastically independent given the approximate flow parameters.