By Xi-Ren Cao
The idea of the operation of many glossy man-made discrete occasion platforms similar to production structures, laptop and communications networks mostly belongs within the area of queuing thought and operations examine. despite the fact that, a few fresh study exhibits that the evolution of those man-made structures demonstrates dynamic gains which are just like these of average actual structures. This monograph offers a multidisciplinary method of the examine of discrete occasion platforms, and is complementary to textbooks in queuing and keep an eye on platforms theories.
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Extra resources for Realization Probabilities: The Dynamics of Queuing Systems
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For example, an invariant set A E Y: is a set for which if w belongs to A, then for all s > 0, the point ~' such that Yt(~') = Yt+~(w) also belongs to A. A process is said to be ergodic if the stationary distribution exists and every invariant set has probability one or zero. Let pt(i) = P(Yt = i) and ptT = (pt(1),pt(2),.. "). 24) Taking the derivative with respect to s, setting s = 0, and applying Kolmogorov's equation yield d T Thus, pT is a stationary distribution of the Markov process if and only if p T ~ = O.
8 Let {Xn} be stationary and Ib(zl, ~2,'" ") be measurable on ¢ ~ , then the process {Yn} defined by Yn -~ ¢(Xn, X n + l , " ") is stationary. ~ P ( X n = j]Xo) = ~r(j), for all j E ~, then the Markov process is said to be asymptotically stationary. -* c~3 for all 9, j E (~. The theorem implies that as n ~ oo, Q" converges to a matrix whose rows are identical. 12), such a Markov chain is aymptotically stationary. 1 A stationary process is not asymptotically stationary when it is periodic. 13)) may exist; the process with a stationary initial distribution is stationary.
A measurable transformation T on f~ --* f~ is said to be measurepreserving, if P ( T - ~ A ) : P(A) for all A C Y. A set A E yr is invarian~ under the transformation T , if T - a A : A. 2 A measure-preserving transformation T on (f~, gz p) is said ~o be ergodic, if for every invariant se~ A, P(A) =0 or 1. Suppose that A is an invariant set and 0 < P(A) < 1. Then starting with w E A, the sequence Tto, T2to, . . can never reach A c, and P(A c) > O. This explains the need for P(A) = 1 or 0. Next, let to' = Tk(to).