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between the corresponding key-space subgroups is large Further, when the deployment points of the two groups of nodes are farther away from each other, the amount of overlap between the corresponding key spaces is very small or even zero The authors then suggest one possible scheme that meets the above requirement In this case, two horizontally or vertically neighboring key-space pools share exactly a fraction a of the key space This fraction a can vary between 0 and 025 Similarly, two diagonally neighboring key space pools share a different fraction b of the key space Even this fraction b varies between 0 and 025 Two nonneighboring key space pools do not share any key spaces We show this in Figure 314 Here the nodes deployed in group E share a fraction a of the keys with the nodes deployed in groups B, D, F, and H Further, they also share a fraction b of the keys with nodes in groups A, C, G, and I In the same gure we describe a possible method proposed in [14] to select key spaces for the subgroups from the global key space pool, assuming a deployment of nodes in 16 subgroups in a 4 4 arrangement In this case, the key spaces for the

found in Theorem 11 of [BEN 97b]; the essential point is the decrease in 2 Hj of the numerator with respect to the scale factor j it is indeed this exponent which governs the almost sure regularity of the process Thanks to the traditional techniques on the random series (see s 15 and 16 of [KAH 85]), we nd that, morally , the trajectories are H lderian of the exponent H On page 34 of [BEN 97b], we will nd a great number of results describing very precisely the properties of the local and overall continuity modules of the elliptic Gaussian random processes; we will only mention here, by way of example, a law of the local iterated logarithm THEOREM 62 If X is an elliptic Gaussian random process of order H, then, for all t , we have: lim sup

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|X(t + ) X(t)| | |H log log( 1 )

= C(t)

(as)

Page 165 steps Figure 83 shows a sample time line schedule with the key milestones included for implementing the customer-based project approach In pursuing an agenda based on such an operating shift, it is important to consider the following steps as vital milestones in making the change a reality: 1 Conducting an honest internal analysis An internal analysis forces us to ask the most basic questions: What are we doing right What do we do better than the majority of our competitors What do our owners expect from us In some cases, the list may be quite long For example, our firm may clearly be the market leader in terms of quality, price, customer satisfaction, and so forth In other circumstances, however, the list may be depressingly short Nevertheless, internal analysis is the key to beginning such a measured corporate change program Until we know where we are, we cannot chart a route to an alternate state

.

(636)

with 0 < C(t) < + Thus, considering that the trajectories are H lderian of the exponent H is equivalent to forgetting the iterated logarithm factor On the other hand, it should be noted that if we are interested only in the continuity module of the elliptic Gaussian random processes, without wanting to specify the limit C(t), then metric entropic techniques (see [LIF 95]) valid for all Gaussian processes are applicable Lastly, elliptic Gaussian processes are locally self-similar and subject to a convergence property of their symbol at high frequency PROPOSITION 62 If an elliptic Gaussian random process X of order H is associated with a symbol verifying: (t, ) = a(t) | | + | |1+2H lim X(t + u) X(t)

t

then X is a locally self-similar of constant multifractional function equal to H:

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