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signi cantly different (Fig. 13.2). The difference in transient loss behavior is only due to the distributions of S and T, which characterize the stochastic properties of the basic time scales in the underlying traf c. We note in Fig. 13.2(b) that if w exceeds some critical value, then the expected loss ratio of the Markov process is less than that of LRD process I. This is due to the effect of the heavy-tailed distributions of S and T . Such an effect becomes more signi cant if C (or B) is large. For example, suppose that we keep B 1 but let C 0:95; see Fig. 13.2(c) and (d). Note that a large C implies a stringent loss performance requirement. In this case, we observe that for any w P 0; B , both the loss measures of the Markov process are less than those of LRD processes I and II. This is because for the Markov process, the transient loss measures decay exponentially fast as C or B increases, but for the LRD processes, the loss measures decay only hyperbolically, due to the LRD effect caused by the heavy-tailed distributions of S and T . The numerical results are consistent with the analytical results regarding transient loss of LRD traf c in single states. As C or B increases, t o and y also increase. According to Theorems 13.3.6



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and 13.3.7, beyond some critical value of t w and y, Markov models can underestimate the loss performance degradation of LRD traf c in on intervals. 13.4 STEADY-STATE LIMITS OF TRANSIENT LOSS MEASURES





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According to some previous studies carried out in steady state, Markov models may still be used for traf c engineering in the presence of long-range dependence. Even though the above conclusion holds in steady state, we still need to examine whether it is valid to extend the conclusion beyond the region of the steady state. To this end, we must know whether loss behavior in the steady state is signi cantly different from that in the transient state. To make an exact comparison between transient loss and loss in the steady state, we consider two-state uid traf c [12]. We have already shown how to compute transient loss measures for two-state uid traf c. Now we show how to compute the steady-state limits of the loss measures, which are de ned by Pflossg lim PflossjR n r1 g

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and E l lim E ljR n r1 :

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