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Proof of Theorem 5.3.1. The plan is to apply Theorem 5.3.2. Note rst that, by Lemma 5.3.3, the variance of L 0; t is nite for all t > 0. Thus, for any nite collection t1 ; . . . ; tn , the nite-dimensional vector L N t1 ; . . . ; L N tn converges weakly to a multidimensional Gaussian distribution, as a consequence of the classical CLT. These nite-dimensional Gaussian distributions satisfy Kolmogorov's consistency criterion, hence the existence of some Gaussian process G with the corresponding nite-dimensional distributions. Lemma 5.3.3 provides bounds on the quantities EjG t G s j2 or order jt sj, which enables us to deduce, by

Kolmogorov's regularity criterion, that a version of G exists with almost surely continuous paths. The version is thus a d-valued random element. We now show that for any interval I 0; T , condition (5.10) of Theorem 5.3.2 is met. Let E be xed as in Lemma 5.3.3. Let t1 t pt2 lie in I . If t2 t1 E, Condition (5.10) is met with p q 2 and F x dx, in view of (5.13). It remains to nd a suitable bound on P N t1 ; t; t2 when t2 t1 > E. Using the basic inequality 2jabj a2 b2 in conjunction with the Cauchy Schwarz inequality, (5.12) entails that P N t1 ; t; t2 This bound is in turn less than 3fEL t1 ; t 4 EL t; t2 4 l t t1 4 l t2 t 4 g: In order to bound the means in the last display expression, note that, by Lemma 5.3.3, both L t1 ; t and L t; t2 are less than the sum of dT =Ee random variables, each of which is less than a Poisson random variable with mean mE. Let m4 denote the fourth moment of such a Poisson random variable. In view of the straightforward P P inequality k ai n k n 1 k jai jn, each of the means in the preceding bound is i 1 i 1 less than dT =Ee dT =Ee4 m4 dT =Ee5 m4 . One thus obtains P N t1 ; t; t2 6fdT =Ee5 m4 lT 4 g: 3 Ex4 EZ4 :

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Networking has changed the face of computing. We once thought of computers as calculating machines, but now most people rightly view them primarily as communication tools. An Internet connection is as essential a part of today's computer as a disk drive. The move toward a globally networked world has been significantly furthered by Java.

Denoting the latter upper bound by K, t2 t1 ! E then entails that P N t1 ; t; t2 K t t1 2 : E2 2

Authentication is all about increasing the level of confidence that can be placed in an identity, source, or message A message can be wrapped in authentication methods to ensure that it is kept secret and has not changed en route to its destination The focus of this authentication is on identity and source, because these aspects relate directly to access and security controls The level of confidence you can routinely place in the identity of an end user, device, or system-to-system process is based on the authentication method Identity answers the question, who are you going to try to authenticate Authentication deals entirely with how you will accept the username as having a sufficient level of genuineness that access to networks, host systems, applications, or data can be granted.

Thus condition (5.10) of Theorem 5.3.2 is met, with p q 2 and F x p d k=E2 x. j 5.3.2 CLT for Rate and Input Processes

Since its birth in the early 1970s as a 12-node network called the ARPANET,3 the Internet has exponentially exploded into a worldwide network that provides a central piece of the planet's information infrastructure. Figure 1.2 shows the growth pattern of the Internet from its humble 12-host beginning through today's some 30-million registered addresses.

The propositions to follow state the functional CLT for the two sequences of processes fL N g and fWt N g introduced in Section 5.2. t Proposition 5.3.5. Let A B denote the total duration of two successive on and off periods of rate process flt g and assume that the distribution of A B has a bounded density in the neighborhood of 0. The sequence of processes Y N de ned by Yt N L N N n t p ; N t ! 0; 5:14

then converges weakly in the space d toward a zero-mean stationary Gaussian process Y with almost surely continuous paths.

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