Deployment architecture

Pipeline Pilot is deployed as a client/server system, with desktop PCs connecting to a central service-oriented architecture deployed on an Apache Web server. The server maintains a repository of components and protocols, in addition to its role as a computational engine. Jobs are spawned to run protocols and provide feedback to the client. These facilities are exposed as standard Web services. 

We run Monte Carlo simulations to examine the performance of the sensor selection algorithm based on the maximization of mutual information for the distributed data fusion architecture. We examine two scenarios first is the sparser one, which consists of 50 sensors which are randomly deployed in the 200 m x 200 m area. The second is a denser scenario in which 100 sensors are deployed in the same area. All data points in the graphs represent the means of ten runs. A target moves in the area according to the process model described in Section 4. We utilize the Neyman-Pearson detector [20, 30] with a = 0.05, L = 100, r) = 2, 2-dB antenna gain, -30-dB sensor transmission power and -6-dB noise power. 

An architecture is, first, an abstraction of a system s implementation. There are many different architectural models that help you understand the system process, module, usage dependencies, and so on. These models help you analyze certain qualities of the system runtime qualities, such as performance, security, or reliability and development-time qualities, such as modifiability and portability. These qualities are important to different system stakeholders not only the end user but also the system administrator, developer, customer, maintainer, and so on. Different kinds of usage scenarios, including system modifications and deployment scenarios, can help you to evaluate architectures against such qualities. 

An architectural description is an abstraction there are many such abstractions that contribute to understanding a system, each one focused on one aspect and omitting other details. As with any model, there is some definition of conformance—that is, does a given implementation conform to that architecture Some views are more focused on the design and development-time activities others are relevant when you re testing or running the system still others focus on deployment and upgrade activities. Table 12.1 shows some useful architectural views and the system parts each one focuses on. 

We can describe this architecture with a combination of a physical model, a component deployment model, and frameworks for the protocols used between these components. Moreover, the four-tier structure itself can be described as a framework. 

PGVL Hub has been well entrenched as one of the key desktop molecular design tools used by Pfizer medicinal chemists. Its solid three-tier enterprise architecture and powerful client-side component easily deployed by Java Web Start provide a very attractive platform with a proven track record for future enhancement and innovations in singleton and library design. There are many possibilities for further enhancement based on user requests as well as attractive methodologies and algorithms already published in the literature (6-27). Here we would like to list a few, with some already being prototyped. 

For most organizations, the following three options exist in regard to deployment architecture. 

Please note that layers and tiers are two different concepts. Tiers mean the physical separation of subsystems—each subsystem runs on a different hardware or the same hardware but in different processes. In a multitiered system, the interaction between the subsystems is accomplished through remote procedure calls (RPCs). Any RPC involves network overhead and therefore has a performance penalty whether the remote procedure is on a separate hardware or on the same physical hardware but in a different process. Layers, on the other hand, are logical separations of the subsystems. Each layer can run on a different physical tier, or all layers can run on a single tier. The purpose of physical tiers is to leverage distributed hardware resources or to reuse a piece of software that is deployed on a different hardware that your system wants to leverage. The purpose of layered software architecture is to separate the system into highly cohesive and loosely coupled modules (see Chapter 2 for software development principles). 

In the context of the Leurre.com project, we have started deploying these platforms all over the world [19]. At the time of this writing, we have deployed 25 platforms, in 5 continents and 12 different countries. We invite the interested reader to look at [20] for a first analysis of this distributed honeypot architecture. 

An earlier version of the DIDB was described in Chapter 14 of the previous edition of this book (5). The new DIDB application launched in 2005 has a typical multitier architecture in a Microsoft . NET environment. The back end is a Microsoft SQL Server 2000 and the current application is deployed on a Web farm. Currently, the database has data extracted from more than 6280 published articles (1966 to 2007) related to drug metabolism and DIs and 260 product labels (1998 to 2007). The use of the Web facilitates worldwide access as well as upgrades and updates the DIDB is updated daily. 

PVK was an early candidate for photoreceptor application. The embodiment deployed in copiers was the complex of PVK with TNF. The mobilities in this system are not suflScient to satisfy the contemporary requirements of high-speed copiers, duplicators, and laser printers. In addition, PVK is too brittle for belt architecture. However, mechanistic studies on this system provide design criteria for closely related MDPs. 

Illustrated by the schematic pictured in Figure 36.4, the subprocess elements we are concerned with in the descriptions that follow are focused on the architecture of the process, not its operation in a specific development program. The focus here is to provide a basis for engineering or reengineering a service, not to describe the performance of the service once it is deployed. 

The PROTECT architecture consists of sensors deployed in various subway stations, complemented by closed-circuit television (CCTV) cameras that have automated and manual pan-tilt-zoom capabilities. These sensor and camera combinations provide data continuously to a centralized chemical-biological emergency management information system (CB-EMIS developed by Argonne National Laboratory) located in a centralized WMATA operations control center. In addition to the sensor and video data from the stations, train operation data and ambient meteorological data are also ported to the CB-EMIS system. Under normal operations, CB-EMIS can provide operator access to the multiple fixed and movable cameras throughout the metro system to assist law enforcement officers or firefighters. It also monitors the status of the sensor systems deployed in the metro. 

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