Page 69 - A First Course In Stochastic Models
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60                    RENEWAL-REWARD PROCESSES

                Substituting E(D tag ) = W q and L q = λW q , the relation becomes

                                                           2
                                                      ρE(S )
                                      W q = λE(S)W q +
                                                       2E(S)
                yielding the Pollaczek–Khintchine formula for W q .


                Rigorous derivation
                A rigorous derivation of the Pollaczek–Khintchine formula can be given by using
                the powerful generating-function approach. Define first the random variables

                   L(t) = the number of customers present at time t,
                    Q n = the number of customers present just after the nth service
                         completion epoch,
                    L n = the number of customers present just before the nth arrival epoch.

                  The processes {L(t)}, {Q n } and {L n } are regenerative stochastic processes with
                finite expected cycle lengths. Denote the corresponding limiting distributions by


                 p j = lim P {L(t) = j}, q j = lim P {Q n = j}  and π j = lim P {L n = j}
                      t→∞                 n→∞                       n→∞
                for j = 0, 1, . . . . The existence of the limiting distributions can be deduced from
                Theorem 2.2.4 (the amount of time elapsed between two arrivals that find the sys-
                tem empty has a probability density and the number of customers served during
                this time has an aperiodic distribution). We omit the details. The limiting probabil-
                ities can also be interpreted as long-run averages. For example, q j is the long-run
                fraction of customers leaving j other customers behind upon service completion
                and π j is the long-run fraction of customers finding j other customers present upon
                arrival. The following important identity holds:

                                                  j = 0, 1, . . . .          (2.5.6)
                                     π j = p j = q j,
                Since the arrival process is a Poisson process, the equality π j = p j is readily veri-
                fied from Theorem 2.4.1. To verify the equality π j = q j , define the random variable
                 (j)
                L n as the number of customers over the first n arrivals who see j other customers
                                                            (j)
                present upon arrival and define the random variable Q n as the number of service
                completion epochs over the first n service completions at which j customers are
                left behind. Customers arrive singly and are served singly. Thus between any two
                arrivals that find j other customers present there must be a service completion
                at which j customers are left behind and, conversely, between any two service
                completions at which j customers are left behind there must be an arrival that sees
                j other customers present. By this up- and downcrossing argument, we have for
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