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Obviously, each di is concave, although, in general, this is not the case for d coincides The concatenation example of two IFS shows that the estimated spectrum d exactly with the theoretical spectrum and exhibits two modes, as is characteristic for phase transition It is important to note that, for a given > 0, it is easy to construct two functions f1 and f2 such that ||f1 f2 ||L2 < or ||f1 f2 || < , yet with very different spectra Therefore, we cannot draw the conclusion that, in general, the original signal spectrum is close to that of the approximating WSA function However, based on criteria which allow us to con rm that the physical properties of the original signal and

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the approximating signal are close, then this conclusion can make sense For example, in the case of speech signals, studied later, an obvious criterion is that of auditory comparison As far as Internet traf c applications are concerned, the chosen criterion will be the comparison between our estimation of the spectrum and that proposed by other approaches Indeed, since approaches are qualitatively different and more or less yield equivalent spectra (as we will see later), this gives credit to the quality of the proposed estimation 910 Experiments The rst example consists of the representation of the word welcome pronounced by a male speaker The signal contains 215 samples, we assume that j0 = 8 and we use the Daubechies-16 wavelet (as explained before, the choice of wavelet is based on the criteria (C1) and (C2)) In this experiment, as in the following one, we assume that (j) = j 2 By using a threshold = 50, we obtain a representation with seven WSA functions, where 64% of the coef cients are processed (the remaining 36% correspond to the tree levels coarser to j0 or to values of cj larger than 1) Figure 98 shows that the original and the approximating k signals are visually almost identical In a more signi cant manner, we cannot distinguish the two signals from an auditory comparison, as can be checked at: http://www-rocqinriafr/fractales In addition, the segmentation (see the crosses in Figure 98) is phonetically consistent, since it coincides almost perfectly with the sounds: silence, /w/, / l /, silence, /k/, /om/, silence The slight difference between the positions of the segmentation marks and the exact transition points between phonetic units is due to the fact that, in our actual implantation, the segmentation is restricted to the dyadic points

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Figure 98 The word welcome pronounced by a male speaker (in black) with its approximation (superimposed in gray) and the segmentation marks (the crosses)

Secure link-state routing protocol (SLSP) [65] is a proposed scheme for securing link-state routing where security is achieved via the use of asymmetric primitives SLSP assumes that each node in the network has a public private key pair Each node broadcasts its certi ed key to all nodes within its zone (ie all nodes that are within R hops from it) These broadcasts are periodic or when conditions require it (eg when there are substantial changes in the network topology), which enables new nodes entering the zone to discover the key Certi cation of public keys can be achieved through a distributed certi cate authority (see 2) We next describe how this scheme works

In the second example, we present an application for Internet traf c signals We use a signal of 512 traf c samples coming out from Berkeley, measured in bytes by time

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steps The analyzed wavelet is Daubechies-4, j0 = 4 and 65% of the coef cients have been processed With a threshold = 30, we obtain two segments Figure 99 shows the original signal (in black), its approximation (in gray), the segmentation marks (the crosses) and the estimated spectrum on each segment (Figure 99b) It is interesting to compare these spectra with those estimated in [LEV 97]: the results are very similar, whereas if we use more segments (or a single segment), a clear difference appears (see Figure 910 for the result obtained with four segments) Since the method used here and that of [LEV 97] are very different, the fact that we have found a concordance can imply that this particular signal possesses two parts, each being stationary in a multifractal sense Such information can be useful for a better understanding of the traf c structure

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Figure 99 (a) Original Internet traf c signal (in black), its approximation (in gray) using two segments and the segmentation marks (the crosses), (b) estimated spectrum for each segment The estimated spectrum for the whole signal is the superior hull of the two curves

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