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More generally, this relation holds for any choice of mother wavelet, which is n supported on [0, 1], provided the multipliers Mk are all identically distributed. This holds because the scaling properties (20.23) of allow us to write the wavelet n 1 coef cients in this case as 2n=2 Mkn . . . Mk1 times a random factor that is i independent of Mki and that is distributed as w0;0 (compare also Bacry et al. [2]). ~ In order to be able to say more about q for the Haar wavelet, we make an assumption that guarantees that the Haar wavelent coef cients don't decay too fast (compare Eq. (20.9)), that is, the prefactor on the RHS in Eq. (20.29) doesn't become too small. Therefore, let us assume in addition that there is some > 0 such that for all n, j2M n 1 1j ! almost surely. Then for all t, n 1 1=n log 2M2kn 1 3 0 , and ~ t 1 lim 1

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Clearly, many of the aforementioned failures will render a media server inoperable. To enable the system to survive a server failure, we will need to introduce hardware/capacity redundancy and fault-tolerant mechanisms into the system. The parallel server architectures in Part II of this book provide one approach to addressing the reliability as well as the scalability challenges.

n3I n log 2 n log 2 n=2 j Ikn j 1 t :

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Restriction enzymes cocktails are used in forensic methods to produce many fragments, so that sequence differences that normally occur between individuals produce many differences in fragment lengths Diagnostic methods employ restriction enzymes that recognize a critical sequence where mutations of this sequence are known to be associated with the disease state The term restriction fragment length polymorphism, abbreviated RFLP, refers to the variety of fragment lengths from DNA digestion with restriction endonucleases The various lengths can result in such distinct electrophoretic separation patterns that they are like ngerprints because they are unique to an individual Simple polymorphisms, such as that seen in Figure 106 with the Mst II site lacking in sicklecell patients, can be employed for diagnostics Figure 107 illustrates the principles of RFLP methods.

20:31

Case #1

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Observe that this is precisely the relation we expect between the scaling exponents of a process and its (distributional) derivative at least in nice cases. Moreover, ~ differentiating Eq. (20.30) and recalling Eq. (20.21), we get T H q 1 T H q , which is in agreement with Eq. (20.31). Thus, both the increment-based and wavelet-based MFA yield the same results for conservative binomial cascades with multipliers bounded away from 1. For a more detailed wavelet-based analysis of 2 conservative cascades, we refer to Gilbert et al. [14] and Riedi [28].

Case #2

While multifractals are new to the networking area, they have been applied in the past mainly for descriptive purposes to such diverse elds as the statistical theory

If the total number of fragments resulting from quantitative digestion is relatively small, the detection step may involve simple ethidium staining directly on the gel, with no Southern blot However, if many fragments are produced, Southern blotting and detection via hybridization with labeled DNA probes are necessary The probes that are chosen hybridize with many fragments, so that a signi cant.

of turbulence, the study of strange attractors of certain dynamical sysems, and, more recently, physical-based rain and cloud modeling; see for example, Evertsz and Mandelbrot [9] and Holly and Waymire [17] and references therein In the networking context, multifractals and their ability to account for time-dependent scaling laws offer great promise for describing irregular phenomena that are localized in time The latter are typically associated with network-speci c mechanisms that operate on small time scales and depending on the state of the network can be expected to have a more or less severe impact on how the packets within individual connections are sent across the network.

Case #3

Empirical evidence in support of complex within-connection or local traf c characteristics in measured wide-area traf c that can be traced to the dominant TCP=IP protocol hierarchy of IP networks has been reported in the original comprehensive analysis of WAN traces by Paxson and Floyd [25] and, more recently, in work by Feldman et al [12] The original ndings of multifractal scaling behavior of measured aggregate WAN traf c are due to Riedi and Levy-Vehel [30] (see also Levy Vehel and Riedi [36]), followed by a similar study by Mannersalo and Norros [24] involving measured ATM WAN traces (for an earlier discussion on multifractal scaling and measured LAN traf c, see also Taqqu et al [35]) Motivated by the empirically observed multifractal scaling behavior in measured WAN traf c by Riedi and Levy Vehel [30], Feldmann et al [11] (see also Gilbert et al.

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