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Finally, in section 5.5, the chapter points out some of the limitations of current approaches, and proposes some research perspectives. In particular, programming paradigms should provide more support to ease programming, heterogenity, as well as scalability issues. Regarding system architectures, real-time aspects, which are not currently well addressed, will become increasingly important for COs. Dynamic maintenance (such as code deployment and run-time update support) is another important issue to address in future systems. Lastly, effort is required to better integrate the various paradigms and systems into a uni ed framework. 5.2. Introduction Key to the successful and widespread deployment of COs and sensor network technologies is the provision of appropriate programming abstractions and the establishment of ef cient system architectures able to deal with the complexity of such systems. Programming abstractions shield the programmer from the nasty system details and allow the developer to think in terms of the concrete application problem rather than in terms of the system. This is also true for traditional distributed systems, where numerous software frameworks and middleware architectures are crucial in performing an integrated computing task. Such frameworks and middleware are based on programming models such as distributed objects or events. These conventional and successful programming abstractions for distributed systems can, however, not be simply applied to COs and sensor networks, due to some substantial differences existing among the latter and the former systems. We will refer to a programming model as a set of abstractions and paradigms designed to support the use of computing, communication and sensing resources in an application and to a system architecture as the structure and organization of a computing system, as a set of functional modules and their interactions . The notion of COs refers to devices ranging from sensors and smart tags to personal computing devices such as cell phones, PDAs or even digital cameras. Within the Embedded WiSeNts project, a CO is formally de ned as a collection of: sensors, controllers (information processors), actuators, or COs that communicate with each other and are able to achieve, more or less autonomically, a common goal . For the purpose of achieving a given global goal, COs can organize themselves in a particular set-up and, like in traditional distributed systems, coordinate and cooperate in order to perform a form of distributed computing. However, traditional distributed
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This section provides a brief introduction to project development. The purpose is to understand the context of the studies that we present later in the chapter. Since the
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Reflection interfaces provide details about the type of the server object at execution time.
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We now have both a larger denominator and a smaller denominator, thus rendering the value for RARORAC less than either RAROC or RORAC. As long as there are risks to be measured, each of these return ratios RARORAC, RAROC, and RORAC will generate a value that is less than expected return divided by capital. And that is the point. A predetermined and clearly specified target (or hurdle) rate of return must be reached to justify any allocation of capital in support of that endeavor; the rate of return must be high enough to cover the costs and capital expenditures needed to support the particular proposal.
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These should be stated concisely and be related to the mission statement. A number of related marketing objectives may be grouped such as promotional objectives.
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Another example of a statistical parameter that is a natural candidate for use in an IT-related environment, is keyboard statistics. Increasingly, at least for the next few years, keyboards will be the predominant way of personally passing information across the network. It would seem logical to investigate whether we can be distinguished, one from another, by the rhythm with which we use the keyboard. There is a respectable history behind this: during the 2nd World War,
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