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Journal ArticleDOI

A tree convolution algorithm for the solution of queueing networks

Simon S. Lam, +1 more
- 01 Mar 1983 - 
- Vol. 26, Iss: 3, pp 203-215
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TLDR
A new algorithm called the tree convolution algorithm, for the computation of normalization constants and performance measures of product-form queueing networks, is presented and is very efficient in the solution of networks with many service centers and many sparse routing chains.
Abstract
A new algorithm called the tree convolution algorithm, for the computation of normalization constants and performance measures of product-form queueing networks, is presented. Compared to existing algorithms, the algorithm is very efficient in the solution of networks with many service centers and many sparse routing chains. (A network is said to have sparse routing chains if the chains visit, on the average, only a small fraction of all centers in the network.) In such a network, substantial time and space savings can be achieved by exploiting the network's routing information. The time and space reductions are made possible by two features of the algorithm: (1) the sequence of array convolutions to compute a normalization constant is determined according to the traversal of a tree; (2) the convolutions are performed between arrays that are smaller than arrays used by existing algorithms. The routing information of a given network is used to configure the tree to reduce the algorithm's time and space requirements; some effective heuristics for optimization are described. An exact solution of a communication network model with 64 queues and 32 routing chains is illustrated.

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Citations
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An algorithm to compute blocking probabilities in multi-rate multi-class multi-resource loss models

TL;DR: An algorithm for computing the (exact) steady-state blocking probability of each class and other steady state descriptions in these loss models is developed, based on numerically inverting generating functions of the normalization constants.
References
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Journal ArticleDOI

Open, Closed, and Mixed Networks of Queues with Different Classes of Customers

TL;DR: Many of the network results of Jackson on arrival and service rate dependencies, of Posner and Bernholtz on different classes of customers, and of Chandy on different types of service centers are combined and extended in this paper.
Journal ArticleDOI

Mean-Value Analysis of Closed Multichain Queuing Networks

TL;DR: It is shown that mean queue sizes, mean waiting times, and throughputs in closed multiple-chain queuing networks which have product-form solution can be computed recursively without computing product terms and normalization constants.
Journal ArticleDOI

Computational algorithms for closed queueing networks with exponential servers

TL;DR: Methods are presented for computing the equilibrium distribution of customers in closed queueing networks with exponential servers based on two-dimensional iterative techniques which are highly efficient and quite simple to implement.
Journal ArticleDOI

Flow Control: A Comparative Survey

TL;DR: Flow control can be exercised at various levels in a packet network: hop level, entry-to-exit level, network access level, and transport level, where the interaction between the different levels is discussed and the most representative techniques are surveyed and compared.
Journal ArticleDOI

A Queueing Network Analysis of Computer Communication Networks with Window Flow Control

TL;DR: A computer communication network with window flow control is modeled by a closed multichain queueing network and the severe computational limitation of previous solution algorithms is overcome with a heuristic derived from the recently found mean value analysis.
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