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Apr 17, 2019 · Want OCR software for free? This article collects the seven best programs that turn images into text.

It is easy to see from Eq. (8.5) that, if process X has spectral density function (8.9), its variance will be equal to (8.7). As o 3 0, from Eq. (8.9) we obtain f o $ const o1 b . We use f x $ g x in the sense that limx3I f x =g x 1. Now we conclude that an exactly second-order self-similar process can be de ned via its autocorrelation function (8.6), variance of the sum (8.7), or spectral density function (8.9), and all these de nitions are equivalent. Meanwhile, for the de nition of an asymptotically second-order self-similar process, it is important to de ne the kind of characteristic to be used. We will use the following de nition. De nition 8.2.2. A stationary process X . . . ; X 1 ; X0 ; X1 ; . . . with nite mean m EXi < I and variance s2 Var Xi < I is called asymptotically second-order self-similar with parameter 0 < b < 1, if



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You re assuming that all clients have nice DNS configurations, and that they ll play by the lifetime and timeout rules, and not make mappings persistent or copy IP addresses into local state files.





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for all k 1; 2; . . . . The sense of this de nition is that, for suf ciently large m, the processes X m will have the same autocorrelation function equal to (8.6). m As we can see from Eqs. (8.1) and (8.5), Var X0 is a double integral of the autocorrelation function or an integral of the spectral density function. These m relations can clarify the behavior of r k , Var X0 , and f o obtained from the real traf c measurements. Usually self-similarity of the data traf c is established by m analyzing the traf c variance Var X0 [5, 12], but the behavior of the variance m Var X0 can be close to a self-similar one, while the behavior of the autocorrelation can be quite different from the theoretical one since the autocorrelation function is a m second derivative of the variance Var X0 . It is also important that, as can be seen from Eq. (8.5), even small harmonics at low frequency can have a dramatic in uence m on the behavior of Var X0 in a suf cient region of m values. 8.3 MODEL OF SELF-SIMILAR TRAFFIC

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I I I I Implicit load balancing doesn t take into consideration the duration of a connection. If every fourth connection is for a rather large file, and all other HTTP hits are for small graphics or HTML files, you ll find that a four-way server farm has a real hotspot where all of the large file transfers cluster. This is an extreme case, but it points to the unpredictability of load balancing via round-robin techniques.

Consider a Poission process on the time axis with intensity l: Let y . . . ; y 1 ; y0 ; y1 ; . . . ;

What started off as a balanced point-counterpoint on DNS round-robin techniques ended up with an extra negative point. This isn t meant to dismiss round-robin DNS out of hand; in some cases it will be the best, quick solution you can implement. However, the Internet market seizes opportunity, and when web server farms became de rigueur, new and established players in IP switching filled the gap in IP traffic distribution.

where yt is the number of Poisson points in the interval t; t 1 ; t 0; 1; 2; . . . . The random variables yt are independent and identically distributed with Prfyt kg lk =k! e l . Suppose that yt is the number of new active sources arriving to the system at moment t. For each source we assign a random variable tt;i the length of the active period, tt;i P f1; 2; . . .g; t 0; 1; 2; . . . ; i 1; 2; . . . and a random process ct;i n the rate of cell generation during the active period at the moment n from the beginning of the period, ct;i n P R ; n 0; 1; 2; . . . . The random couples tt;i ; ct;i n are independent and identically distributed and also independent of the process y. We de ne our process Y . . . ; Y 1 ; Y0 ; Y1 ; . . . as Yt

Network redirection is essentially a reliable DNS round-robin service in a box. An IP redirector assumes a well-known, public hostname and IP address, and then translates it into multiple back-end, private IP addresses. When combined with routing functions, the IP redirector can talk to back ends on multiple networks. Figure 9.9 shows a typical IP redirector configuration, using a redundant IP switch to avoid a single point of failure at the public/network interface. There are several variations on the basic redirector idea, ranging from simple IP address load balancers to stateful, packet-inspecting switches that perform load balancing and failover between back-end targets based on session information.

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