Heterogeneous switch architectures in .NET Encoding barcode pdf417 in .NET Heterogeneous switch architectures

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15.6 Heterogeneous switch architectures use vs .net pdf417 printing togenerate pdf417 2d barcode in .net ISO/IEC 18004:2000 Fig. 15.7.

PDF-417 2d barcode for .NET Channel distribution across trunks as viewed by two nodes employing different switching architectures..

in exactly t trunks being available. This value is computed using the following:. t t min( f 1 ,S2 ) min( f 2 ,S2 ). t 1 (t 1 Visual Studio .NET pdf417 2d barcode , u 1 x, u 2 y) 1 (1, x, y). t (t , f 1 , f 2 ) =. if t > 0 and u 1 > 0 min( f2 ,S2 ) t 1 (t, f 1 , f 2 y) 1 (1, x, y) y=1 if t = 0 and u 1 = 0 (15.47). It has to be noted that the computation of the probability P(T3 , T4 T1 , T2 , .NET pdf417 2d barcode f 1 , f 2 ) does not depend on T1 and T2 . Case 2: architecture-dependent mapping.

This choice arises from an architectural viewpoint. Note that when a link has multiple bers, wavelengths, and time slots, the alternatives for trunk switching are limited to treating either the wavelength or the time slot as a trunk, when only limited switching is allowed. In such a case, two nodes that view the link differently would have the channel distribution as considered here.

For example, consider a link with two wavelengths and three time slots per wavelength. Let node 1 view the link as wavelength trunks, i.e.

two trunks with three channels in each. Let node 2 view the link as time-slot trunks, i.e.

three trunks with two channels in each. This scenario is depicted in Fig. 15.

7 showing the distribution of channels across trunks as seen by the two nodes. In this case, due to the regularity in the channel distribution, the knowledge of the trunk and channel distribution as seen by node 1 could be used to derive the lower bound on the trunk distribution as seen by node 2. For example, if three channels are free with one trunk being free as viewed by node 1, then a minimum of three trunks need to be free as viewed by node 2.

In general, if f 1 channels and T1 ( f 1 > 0 and T1 > 0) trunks are free, then a minimum of f 1 K 2 /T1 S1 trunks must. Blocking in TSN be free as .net vs 2010 PDF-417 2d barcode viewed by the second node. Recall that K 2 denotes the total number of trunks in a link as viewed by node 2 and S1 denotes the number of channels per trunk as viewed by node 1.

The same reasoning is true for the lower bound on the available trunks as well. The required probability P(T3 , T4 . T1 , T2 , f 1 , f 2 ) is then computed by setting the probability values of those trunk distributions that are not feasible to zero, speci cally P(T3 , T4 . T1 , T2 , pdf417 2d barcode for .NET f 1 , f 2 ) is set to 0 if one of the following holds true: T1 > 0 T2 > 0 and and T3 < T4 < f1 K 2 T1 S1 f2 K 2 T2 S1 (15.48) (15.

49). The probabi lities are then normalized to set the sum of all the conditional probabilities to 1. This pruning of state-space depends entirely on the architecture, hence it will be different for different architectures. 15.

7 Improving the accuracy of the analytical model It can be observed that the analytical model is developed based on a two-level approach. First, the channel distributions are considered to evaluate trunk distributions at nodes and mapping probabilities. Employing these trunk distribution and mapping probabilities, the blocking performance on a path is obtained.

The computation of the blocking performance on a path does not explicitly include the channel distribution on the link. Hence, the analytical model developed in this case is not an exact computation of the blocking performance. However, in the next chapter it is shown that suf cient accuracy is obtained in estimating the path and tree blocking performance.

Some of the interesting features that are exhibited by networks cannot be observed if the analytical model is evaluated only once. For example, if a network rejects a larger number of calls that travel longer distances compared to another network, then it would accept a larger number of calls that travel shorter distances. In order to obtain the ner behavior, the analytical model needs to be evaluated more than once by adjusting the parameters based on the results obtained in the earlier runs.

The two main input parameters to the analytical model are the link load and link load correlation. The computation of these two parameters is described in detail in the next chapter. When calls are rejected by the network, these two parameters are affected.

The link load and link load correlation experienced by the network are only due to the calls that are accepted in the network. Hence, blocked calls do not have any effect on these parameters..

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