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Theorem 6.5.3. Consider the stable GI =G=I FCFS queue with A t and B t speci ed by Eqs. (6.48) and (6.49). If the tail of A(t) is heavier than that of B(t), then the ``contracted'' waiting time DA r W =a converges in distribution for r 4 1, the limiting distribution is the negative exponential distribution with unit mean and LST 1= 1 r , and the coef cient of contraction DA r is that root of the equation Ca xna 1 La x 1 r; x > 0; 0 < 1 r << 1; 6:56

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with the property that DA r 5 0 for r 4 1. Theorem 6.5.4. Consider the stable GI =G=1 FCFS queue with A t and B t speci ed by Eqs. (6.48) and (6.49). If A t and B t have similar tails and na nb 2, then the ``contracted'' waiting time DAB r W =a converges in distribution for r 4 1, the limiting distribution is the negative exponential distribution with unit mean and LST 1= 1 r , and the coef cient of contraction DAB r is that root of the equation Ca xLa x Cb rxLb x 1 r; with the property that DAB r 5 0 for r 4 1. The previous three theorems give conditions under which DW converges in distribution. D appears to be of order (roughly) 1 r 1= min na ;nb 1 . The limiting distribution is exponential when the interarrival time distribution is heavier, and is a heavy-tailed distribution Rn 1 t (which is related to the Mittag Lef er function) when the service time distribution is heavier. It should be noted that R1=2 t p 1 et erfc t . The complementary error function erfc x is a special function that has been investigated in much detail; this has resulted in considerable insight into the behavior of the limiting distribution in this special case (cf. Boxma and Cohen [10]). The most complicated case occurs when r 4 1 while A t and B t have similar tails, with 1 < n : na nb < 2. We introduce the following notation. Let da : with D : Let F r a : 1 2pi iI

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