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In
queueing theory Queueing theory is the mathematical study of waiting lines, or queues. A queueing model is constructed so that queue lengths and waiting time can be predicted. Queueing theory is generally considered a branch of operations research because th ...
, a discipline within the mathematical
theory of probability Probability theory or probability calculus is the branch of mathematics concerned with probability. Although there are several different probability interpretations, probability theory treats the concept in a rigorous mathematical manner by expre ...
, the Gordon–Newell theorem is an extension of Jackson's theorem from open queueing networks to closed queueing networks of exponential servers where customers cannot leave the network. Jackson's theorem cannot be applied to closed networks because the queue length at a node in the closed network is limited by the population of the network. The Gordon–Newell theorem calculates the open network solution and then eliminates the infeasible states by renormalizing the probabilities. Calculation of the
normalizing constant In probability theory, a normalizing constant or normalizing factor is used to reduce any probability function to a probability density function with total probability of one. For example, a Gaussian function can be normalized into a probabilit ...
makes the treatment more awkward as the whole state space must be enumerated. Buzen's algorithm or mean value analysis can be used to calculate the normalizing constant more efficiently.


Definition of a Gordon–Newell network

A network of ''m'' interconnected queues is known as a Gordon–Newell network or closed Jackson network if it meets the following conditions: # the network is closed (no customers can enter or leave the network), # all service times are exponentially distributed and the service discipline at all queues is FCFS, # a customer completing service at queue ''i'' will move to queue ''j'' with probability P_, with the P_ such that \sum_^m P_ = 1, # the utilization of all of the queues is less than one.


Theorem

In a closed Gordon–Newell network of ''m'' queues, with a total population of ''K'' individuals, write \scriptstyle (where ''k''''i'' is the length of queue ''i'') for the state of the network and ''S''(''K'', ''m'') for the state space :S(K,m) = \left\. Then the equilibrium state probability distribution exists and is given by :\pi (k_1,k_2,\ldots,k_m) = \frac \prod_^m \left( \frac \right)^ where service times at queue ''i'' are exponentially distributed with parameter ''μi''. The normalizing constant ''G''(''K'') is given by :G(K) = \sum_ \prod_^ \left( \frac \right)^ , and ''e''''i'' is the visit ratio, calculated by solving the simultaneous equations :e_i = \sum_^m e_j p_ \text1 \leq i \leq m.


See also

* BCMP network


References

{{DEFAULTSORT:Gordon-Newell theorem Theorems in probability theory Queueing theory