27 Web Services Modeled Using a Hierarchical Client–Server Flow Model This type of flow model can also be seen with the visualization application group described in Chapter 2. An example of this is in the visualization of scientific simulations. Consider the simulations of a multipart problem. These can be found in climate modeling, fluid flow analysis, structural analysis, and others. In climate modeling there may be a simulation consisting of multiple parts- atmosphere, earth, and ocean-as shown in Figure 4.28. Each part of the simulation in this figure may be developed on a separate computing device, probably at different locations (based on where the various scientists are located). Since each component affects the others, at the boundaries between atmosphere, earth, and ocean, data must be passed between the computing servers for each part. The flows would look like those in Figure 4.29. In this figure, if the parts of Earth Systems Ocean Systems Atmospheric Systems FIGURE 4.28 Components of a Climate Modeling Problem 188 CHAPTER 4 Flow Analysis Server Server Earth Model Scientists (Earth Model) Scientists (Ocean Model) Ocean Model Atmospheric Model Scientists (Atmospheric Model) Server FIGURE 4.29 A Hierarchical Client–Server Model for Scientific Visualization the simulation are being solved at different locations, then the servertoserver flows may cross long (WAN) distances, impacting both local and widearea networks. 4.6.4 DistributedComputing The distributedcomputing flow model, shown in Figure 4.30, is the most specialized of the flow models. A distributedcomputing flow model can have the inverse of the characteristics of the client–server flow model, or a hybrid of peertopeer and client–server flow models. In this model, flows may be primarily between a task manager and its computing devices (like a client–server model) or between the computing devices (like a peertopeer model). The type of model depends on how the distributed computing is done. The important characteristics of this model are that the flows can be client–server but are reversed in direction, and that the computing devices may have strict performance requirements. We can make distinctions in the distributedcomputing flow model based on the relationship between the task manager and the computing devices and what the task is. This relationship can result in the computing devices being closely coupled, where there are frequent transfers of information between devices, or loosely coupled, where there may be little to no transfer of information between computing devices. Tasks may range from having a coarse granularity, where each task is dedicated to a single computing device, to having a fine granularity, where a task is subdivided among several devices and the computing is done concurrently. Flow Models 189 Computing Nodes Are Data Sources and Sinks Computing Node Computing Node Computing Node Request Request Request Response Response Response Task Server Is Likely Data Sink Task Server Interaction Interaction Interaction FIGURE 4.