Today many countries are aiming for the establishment of national information infrastructures in order to satisfy the emerging needs of the upcoming information society. This infrastructure should provide the foundati...
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Today many countries are aiming for the establishment of national information infrastructures in order to satisfy the emerging needs of the upcoming information society. This infrastructure should provide the foundation of an "electronic marketplace", where information services and telecommunication services will be offered by competitive service providers to arbitrary customers. The rapid and customized provision of services, which we call "intelligence on demand" represents an important prerequisite for the realization of a dynamic market place. In this context the concept of "mobile service agents" offers a new paradigm for the rapid and customized provision of services in open distributed processing environments. We illustrate the differences between telecommunication services based on the traditional, i.e. RPC-based client/server paradigm, and service implementations based on mobile service agents. We also discuss architectural principles and requirements of a distributed agent environment supporting mobile service agents. To show the benefits of mobile agent technology and specifically its application for the realization of mobile service agents, the paper addresses the impact of the mobile service agent concept on existing and upcoming telecommunication architectures such as IN, TMN and TINA.
The paper describes engineering a system for a distributed Austrian Alpine road-pricing environment as well as the structure and organization of the software development. The client/server-based road-pricing system, h...
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The paper describes engineering a system for a distributed Austrian Alpine road-pricing environment as well as the structure and organization of the software development. The client/server-based road-pricing system, handling on average 1.2 million vehicle transitions per month, had be to operational within a mere eight months after the start of the project. Current practical and industrial problems of client/server system strategies are discussed. Our main theses derived from the presented case study are: in current medium to large software engineering tasks there is a need for a) technical specialists for industrially identified project stress points (database, network, front-end) with experience in large projects, b) a project and process plan for a (very) short development time frame before production, and c) a dynamic production-oriented process model rather than a traditional linear process model.
The application of artificial neural networks (ANN) in real-time embedded systems demands high performance computers. Miniaturized massively parallel architectures are suitable computation platforms for this task. An ...
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ISBN:
(纸本)0780320182
The application of artificial neural networks (ANN) in real-time embedded systems demands high performance computers. Miniaturized massively parallel architectures are suitable computation platforms for this task. An important question which arises is how to establish an effective mapping from ANN algorithms to hardware. In this paper, we demonstrate how an effective mapping can be achieved with our programming environment in close combination with an optimized architecture design targeted for neuro-computing.
This paper proposes an object oriented method applied to the design of network protocols, telecommunication services and network management information architectures. This method is based on the concept of object orie...
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This paper proposes an object oriented method applied to the design of network protocols, telecommunication services and network management information architectures. This method is based on the concept of object oriented generic models. A generic model is a common structure applicable to the design of all the components of a given application. Generic models are proposed for each of the considered application domains.
Heterogeneous processing systems have long been used for the design of avionics architectures. Until recently, this architecture took the form of federated or 'black box' systems. Advanced architectures, chara...
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Heterogeneous processing systems have long been used for the design of avionics architectures. Until recently, this architecture took the form of federated or 'black box' systems. Advanced architectures, characterized by terms such as integrated, open systems, and modular avionics, are now being adopted by the DoD. Consistent with new hardware designs, are burgeoning software technologies. These include megaprogramming, and programming in the large, and object-oriented development, and a host of design methodologies. This paper attempts to reconcile these often divergent technologies given the real-time rigors of Digital Signal Processing (DSP) applications and the mandate to use the Ada programming language. Beginning with an overview of the state of DSP and software methodologies, Ada program building blocks are then presented with the unique intent of defining reusable software components for any platform of heterogeneous distributed embedded processors.
Nonlinear system behavior is not always well characterized by linear or linearized system models, especially if the system is rapidly time-varying and/or is chaotic. Model paradigms that are themselves nonlinear, such...
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ISBN:
(纸本)0780325605
Nonlinear system behavior is not always well characterized by linear or linearized system models, especially if the system is rapidly time-varying and/or is chaotic. Model paradigms that are themselves nonlinear, such as neural networks, potentially offer more accurate and more robust models for these nonlinear systems. This research studies the use of a neural network structure to model a linear system and two nonlinear systems, a quadratic system and a chaotic system. Several training algorithms are used, including traditional back propagation, an evolutionary programming approach, and a hybrid approach. Net architectures studied here consist of a traditional feed forward topology and a radial basis topology. Modified back propagation training using a feed forward network proved adequate for modeling the linear and quadratic systems, but these were hopelessly inadequate in modeling the chaotic system. The radial basis net fared better, but was still a poor performer for projecting the chaotic system beyond the observed data.
We propose two new concepts, evolutional agent and field. The main purpose of the work is to provide a framework for building software which adapts to changes of requirements autonomously. In opennetworks, the adapta...
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Traditionally, the problems of binding and placement in the synthesis of digital circuits have been formulated and solved separately. However, placement and binding strongly interact and design decisions taken during ...
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Traditionally, the problems of binding and placement in the synthesis of digital circuits have been formulated and solved separately. However, placement and binding strongly interact and design decisions taken during these phases determine the interconnect structure. As feature sizes continue to decrease, the delay caused by signal propagation through interconnect more and more dominate the overall system performance. Hence, optimizing interconnect becomes increasingly important. In this paper, we propose for the first time an analytical approach to capture the placement and binding problems in a single, unified Mixed Integer Linear programming (MILP) model which also allows minimizing the overall interconnect structure. Such a model can serve as a starting point for deriving efficient heuristics in that it captures all information required for a comprehensive analysis of the problem. The target architecture is a linear bit-slice datapath, however, the model can be easily extended to handle two-dimensional datapath models.
The application of artificial neural networks (ANN) in real-time embedded systems demands high performance computers. Miniaturized massively parallel architectures are suitable computation platforms for this task. An ...
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The application of artificial neural networks (ANN) in real-time embedded systems demands high performance computers. Miniaturized massively parallel architectures are suitable computation platforms for this task. An important question which arises is how to establish an effective mapping from ANN algorithms to hardware. In this paper, we demonstrate how an effective mapping can be achieved with our programming environment in close combination with an optimized architecture design targeted for neuro-computing.< >
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