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By breaking up huge amounts of data into bite-sized pieces, and sharing them among millions of computers, they have achieved the same goals as the developers of grid computing initiatives The grid is seen by some as the next step in the evolution of computing: a model where all computers in a particular logical or physical region (a data center, a company, a country, or perhaps the whole world) are joined together to share computing resources Systems with idle resources would make those resources available to the rest of the grid Proponents of grid computing often speak of a utility model for computing, where you could plug an appropriate device into the wall, just as you would plug in a table lamp to get electricity, and you would receive computing cycles.



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p then converge weakly as y 4 I toward process l fZt g, where fZt g is an FBM with Hurst parameter H and l is de ned in Eq. (5.34). Proof. To ensure the convergence of the sequence of centered Gaussian processes fZt y g, one could, for instance, rely on Theorem 5.3.2. Here we content





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That appropriate device would probably be a computer, without a great deal of processing power, but just enough to know how to successfully connect to the grid and communicate with it Before grid computing can achieve wider acceptance, there are many hurdles that will need to be cleared, the biggest of which is probably security If someone else can run a process on my system, who s to say that the process won t work some mischief on my system and steal passwords or install some form of malware At the same time, if my process runs on some anonymous.

Therefore, G r* s a 2 1 b 1 2 1 s 2 =2 1 b : 2 s 2 2 1 b 11:19

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The Mellin transform p* s therefore has a singularity set made of simple poles sk b 4i 1 b kp =2, for k integer. As we saw in the tutorial section about the Mellin transform, this kind of set creates periodic uctuating terms in front of the polynomial expansion. This periodic uctuation is re ected in the asymptotics of pn , namely: pn b a lv1 v1 v0 log 2 v1 v0 l 1 P 1 b G sk exp 4ikp log n n b O n b e : log 2 k

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In other words, we have proved that pn P log n n b , where P is a periodic function, of period log 2= 1 b , whose Fourier coef cients are proportional to G sk . Since function P is not constant (indeed Fourier coef cients are all nonzero), we don't have lim inf P x lim sup P x . Figure 11.4 displays function r x computed for b 0:5, which causes uctuating polynomial coef cients. 11.3.3 A Multiplexer Queue Under an In nite Number of On=Off Sources

system, who s to say that the other system won t in some way affect (either innocently or maliciously) the running of that process and cause it to return bad data, or to snoop on what the process is doing One argument against the grid is that today s computers already have far more processing power than their owners actually need, and that PDAs and portable phones will likely follow suit before too long With that in mind, grid architectures may only be useful for a handful of the most overwhelmingly processing-intensive applications, such as weather forecasting, factoring prime numbers, and SETI@home-like projects Another important concern that must be addressed before grid computing can achieve wide acceptance is accurate process billing If you are running a process on my computer, I would certainly expect you to pay me for the resources you are consuming.

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In the previous section we considered on=off sources served by separate parallel queues. In this section we consider that all on=off sources forward their packet to a

If grid resources become truly worldwide, political questions come into play as well: What if a process sent from one country is run on a computer in a country where the process is illegal in some way, and how can these concerns be policed Is it appropriate for one company to run processes on computers owned by a competitor Policy and resource allocation, as discussed in 19, will prove to be a fundamental enabler for large-scale grid computing Early-adopting commercial entities must begin to implement small grids internally to make better use of their existing computing resources To be fair, at this writing there are very few commercial applications that can take advantage of the grid New techniques must be developed to encourage the production of parallel applications, as well as distributed applications for highly partitioned computing.

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