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business processes, comprising multiple steps with asynchronous and uni-directional interactions which function on independent platforms. For example, consider three applications, one to take an order, one for managing customers, and one for managing sales. Each application operates on different platforms and uses technologies appropriate to those platforms, and each uses information about enterprise customers. Consistency of information among these three applications must be ensured. Two methods can be used: The repository approach: copy the data directly from the database (or from files) used by the original (order-taking) application to the databases (or files) used by the other two applications (Figure 2.7). This approach goes through the data. It presupposes that the semantic and data models used by the applications are compatible. Furthermore, it does not preserve the integrity of the data from the recipient applications since it does not make it possible to apply the update logic and management rules of those other applications.

reliability is greatly reduced. Adding this level of certainty to network services requires knowing how and why they break.

Once substrate has arrived in the reaction layer, simple one-substrate Michaelis Menten kinetics (Eq. 7.5 for oxidoreductase enzymes, where EO and ER represent oxidized and reduced enzyme, respectively) yield uxes for the formation of the enzyme substrate complex (jC ) and the decomposition of this complex to form product (jP ), Eqs. 7.6 and 7.7:

Network failures create frustration because of the myriad failures possible when you combine host interfaces, cables, switches, routers, hubs, and network services like Dynamic Host Configuration Protocol (DHCP) or Domain Name Service (DNS) Understanding the different possible failures for a network of systems is critical for ensuring its availability; while you may not be subject to all of the corner cases, you need to know which ones are potential traps and how you ll avoid or manage your way out of them Some of the most common network failures are: Local network interface Typically on an I/O card with one or more network interfaces, the network interface represents the first point of potential failure between a host and the outside world.

7:5 7:6 7:7

An I/O bus or partial backplane failure can make a network interface appear to have failed; however, these system-level failures usually cause other more easily noticed problems such as disk I/O failures or complete system crashes In rare cases, devices on the I/O card fail, and the network interface is rendered inoperable Cabling Items subject to the highest degree of physical wear and tear tend to fail the most frequently Cables connecting hosts to hubs or switches are near the top of this category, with failures that include a broken locking clip, causing the cable to fall out of the connector; a frayed conductor in the cable; or severe physical strain resulting in damage Network infrastructure equipment Hubs, switches, bridges, and other devices that sit below the IP layer are frequent contributors to networklevel failures.

It s not just physical failures that should give you pause; excessive load may cause packets to be dropped on the inbound side of a switch, resulting in an intermittent network outage Routers and route information At the IP layer, software, configuration, and even interoperability woes are also root causes of network outages In 1998, AT&T lost part of a frame relay (FR) network due to a misconfigured router, resulting in a multiple-hour outage for some of its FR customers Physical failures remain a possibility; however, IP networks are typically designed with some level of redundancy to handle router failures That redundancy, reflected in the routing tables of hosts, is yet another source of network outages Key network services Even the simple act of deriving an IP address corresponding to a hostname requires talking to another host on the.

These uxes are simply the homogeneous reaction rates multiplied by the thickness of the enzymatic reaction layer, as given in Eq. 7.1.

You can attempt to strike a balance between transaction size and recovery time Consider the difference between a transaction that updates every customer record in a single SQL statement and one that walks through the index sequentially, updating each record as a separate transaction Clearly, the second approach takes longer, as it eliminates any benefits of caching and bulk data retrieval that the database might perform for you Large transactions are the norm, but they aren t always the easiest to recover Database crashes between separate transactions mean the client program can pick up where it left off, possibly repeating the one transaction that was inflight at failure time This requires that client-side applications know how to walk through the table, and also how to determine what the pickup point is; a client-side crash will require the application to query the database to find its last update.

The event-based approach: transmit an event from the original application to the other two applications, which will then ensure its processing, updating their own information themselves (Figure 2.8). No matter which method is used, data can be copied or events transmitted in sessions (batches to copy information or send events) or in real time (copy or send each process performed in the original application).