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This is a fairly math-heavy section If math is not your strong suit, you can safely skip it But please take away our conclusions: There are many technologies that make great sense to implement to increase availability, even in less critical environments As your needs for availability increase, you will need to implement more expensive and more complex protective technologies Not every system needs those technologies; it depends where the systems fall on the Availability Continuum, as presented in the next section As we discussed in 2, What to Measure, the following is the formula for availability: MTBF A= MTBF + MTTR There are two ways, based on that formula, to improve availability Either extend MTBF (keep the systems components from failing) or extend MTTR (shorten the recovery time when they do fail) The easier one for system administrators to affect is, of course, MTTR.

This classical model works well for small, inorganic ions, but does not adequately describe the interactions of biological macromolecules, such as proteins and nucleic

Components are going to fail when they fail; it is difficult to significantly influence how often they fail If you approach the problem with the basic premise that some outages and downtime are inevitable, you can seriously reduce your downtime by taking steps to minimize the duration of your outages By mirroring disks, for example, you can reduce the downtime caused by a failed disk from hours to zero By setting up clustering and failover, you can reduce downtime from a systemwide hardware failure from (potentially) days to just a few minutes If you have only one outage in a particular week, and you can reduce its duration from 4 hours to just 10 minutes, you have increased availability for that system during that week from 976 percent to better than 999 percent.

As we ve said, implementing protective measures costs money, but consider the example in the previous paragraph If the cost of downtime for the system in question is $100 per minute (a reasonable and often low number), reducing the outage s duration from 240 minutes (4 hours) to 10 minutes saves the company $23,000 If you could expect this outage to occur once a month, then implementing this one protective measure can save the company $276,000 per year.

acids, with ion-exchange resins. With these polyelectrolyte species, electrostatic interactions do not follow simple stoichiometric laws, and the multiple charges are not all simultaneously accessible to the ion-exchanger. For this reason, a more elaborate model has been developed to account for the behavior of polyelectrolytes. 14.8.1. Retention Model for Ion-Exchange Chromatography of Polyelectrolytes13 An expression relating the capacity factor k Vr Vo =Vo (and Eq. 14.3) to the Gibbs free energy of retention, Gret, has been developed as a general relation that applies to all retention mechanisms. This expression is shown in Eq. 14.27: ln k Gret =RT ln f 14:27

4.3.4. Inter-enterprise exchange platforms From the point of view of individual participating enterprises, the problems linked to exchanges with partners may vary, but they all relate to heterogenity. A large enterprise whose information system uses a distributed architecture, must overcome the challenges linked to the need for connecting partners of quite different types: small enterprises, who do not often have deep information technology competence, particularly where it concerns networks; medium enterprises, also with limited competencies, but who can still exchange information electronically on simple, low-cost infrastructures; large enterprises or groups, with significant computing services with strong competencies in the domain of the electronic exchanges, but from this fact, also have a tendency to want to dictate the technologies that they will use. In most cases, because these connections are carried out without using an organized approach, the result (Figure 4.10) will generate numerous problems:

Would it be worth spending $25,000 to achieve these savings Would it be worth spending $200,000 Would it be worth spending $500,000 What if the life span of the system (and therefore the investment) were 5 years What if the cost of downtime for the system were $500 per minute What if we could only reduce the outage from 4 hours to 2 hours If we apply some arithmetic to these questions, we can come up with some fairly concrete answers For this analysis, we will look to reduce the risk of downtime In the analysis, the goal is to evaluate the potential savings after we apply a particular protective measure, when we compare the current situation to the situation we are thinking about implementing So, Savings (S) equals Risk Before (RB) minus Risk After (RA) Mathematically, that s S = RB RA..