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Earlier in this chapter, I discussed various physical architectures in which different parts of an application might run on different machines. With a high-scalability smart client architecture, for example, there will be a client, an application server, and a data server. With a high-security web client architecture, there will be a client, a web server, an application server, and a data server. Parts of the application will run on each of these machines, interacting with each other as needed. In these distributed architectures, you can t use a straightforward object-oriented design, because any communication between classic fine-grained objects on one machine and similar objects on another machine will incur network latency and overhead. This translates into a performance problem that simply can t be ignored. To overcome this problem, most distributed applications haven t used object-oriented designs. Instead, they consist of a set of procedural code running on each machine, with the data kept in a DataSet, an array, or an XML document that s passed around from machine to machine. This isn t to say that object-oriented design and programming are irrelevant in distributed environments just that it becomes complicated. To minimize the complexity, most distributed applications are object-oriented within a tier, but between tiers they follow a procedural or service-based model. The end result is that the application as a whole is neither object-oriented nor procedural, but a blend of both. Perhaps the most common architecture for such applications is to have the Data Access layer retrieve the data from the database into a DataSet. The DataSet is then returned to the client (or the web server). The code in the forms or pages then interacts with the DataSet directly, as shown in Figure 1-15.

q.DeleteMessage(msg); if (useGradualDecrease) if (currentInterval > intervalFloor) currentInterval = currentInterval / 2; else currentInterval = intervalFloor; else currentInterval = intervalFloor; } else { if (currentInterval < intervalCeiling) currentInterval = currentInterval * 2; Thread.Sleep(currentInterval * 1000); } }

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The final step in the object design process is to compare the new class diagram with the original use case descriptions in order to ensure that everything described in each use case can be accomplished through the use of these objects. Doing so helps to ensure that the object model covers all the user requirements. The complete object model is shown in Figure 6-9, with the updated CRC information shown in Table 6-3. The solid-lined arrows in Figure 6-9 indicate collaboration between objects, illustrating how many of them work together to provide the required functionality. The dashed lines show navigation between objects. For instance, if you have a ProjectInfo object, it is possible to navigate from there to a Project, typically by calling a GetProject() method. While navigation between objects isn t strictly necessary, it is often of great benefit to UI developers. Consider that a UI developer will get access to a ProjectInfo object when the user selects a project from a control in the UI. In most cases, the next step is to load the associated Project so that the user can view or edit the data. Providing navigational support directly in the object model makes this trivial to implement within the UI.

For example, suppose the start value for the delay loop was 2 seconds. After an empty poll, the length would be doubled to 4 seconds. Successive empty checks would result in the time delay increasing to 8, 16, 32, 64, 128, 256, and 512 seconds. You can see the code that produces this progression at w. Figure 16.9 shows how the delay is increasing in this example as the queue remains empty. At 512 seconds, the counter reaches the maximum set for the system, so it doesn t rise above 512 seconds. After some time a message appears. The system processes the message, and then checks the length of the queue. Because there was activity on the queue, the delay setting is set to the next step down the ladder, to 256 seconds at line q. The code also supports an immediate drop to the floor interval if you want an aggressive increase in the rate of polling. Figure 16.9 shows the backoff polling in action. The sample code will randomly put messages in the monitored queue there s a one-in-three chance of it doing so. The interval started at 2 seconds, and was immediately bumped to 4. Then a message was processed, so it was dialed back down to 2. Then there was a succession of empty calls, leading the code to rapidly increase the polling interval all the way up to 16 seconds between checks.

Project ProjectResources ProjectResource Resource ResourceAssignments ResourceAssignment Assignment ProjectList ProjectInfo ResourceList ResourceInfo RoleList Roles Role

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