100,523 research outputs found

    Slisp: A Flexible Software Toolkit for Hybrid, Embedded and Distributed Applications

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    We describe Slisp (pronounced ‘Ess-Lisp’), a hybrid Lisp–C programming toolkit for the development of scriptable and distributed applications. Computationally expensive operations implemented as separate C-coded modules are selectively compiled into a small Xlisp interpreter, then called as Lisp functions in a Lisp-coded program. The resulting hybrid program may run in several modes: as a stand-alone executable, embedded in a different C program, as a networked server accessed from another Slisp client, or as a networked server accessed from a C-coded client. Five years of experience with Slisp, as well experience with other scripting languages such as Tcl and Perl, are summarized. These experiences suggest that Slisp will be most useful for mid-sized applications in which the kinds of scripting and embeddability features provided by Tcl and Perl can be extended in an efïŹcient manner to larger applications, while maintaining a well-deïŹned standard (Common Lisp) for these extensions. In addition, the generality of Lisp makes Lisp a good candidate for an application-level communication language in distributed environments

    Design and Performance Analysis of a Non-Standard EPICS Fast Controller

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    The large scientific projects present new technological challenges, such as the distributed control over a communication network. In particular, the middleware EPICS is the most extended communication standard in particle accelerators. The integration of modern control architectures in these EPICS networks is becoming common, as for example for the PXI/PXIe and xTCA hardware alternatives. In this work, a different integration procedure for PXIe real time controllers from National Instruments is proposed, using LabVIEW as the design tool. This methodology is considered and its performance is analyzed by means of a set of laboratory experiments. This control architecture is proposed for achieving the implementation requirements of the fast controllers, which need an important amount of computational power and signal processing capability, with a tight real-time demand. The present work studies the advantages and drawbacks of this methodology and presents its comprehensive evaluation by means of a laboratory test bench, designed for the application of systematic tests. These tests compare the proposed fast controller performance with a similar system implemented using an standard EPICS IOC provided by the CODAC system.Comment: This is the extended version of the Conference Record presented in the IEEE Real-Time Conference 2014, Nara, Japan. This paper has been submitted to the IEEE Transactions on Nuclear Scienc

    A distributed agent architecture for real-time knowledge-based systems: Real-time expert systems project, phase 1

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    We propose a distributed agent architecture (DAA) that can support a variety of paradigms based on both traditional real-time computing and artificial intelligence. DAA consists of distributed agents that are classified into two categories: reactive and cognitive. Reactive agents can be implemented directly in Ada to meet hard real-time requirements and be deployed on on-board embedded processors. A traditional real-time computing methodology under consideration is the rate monotonic theory that can guarantee schedulability based on analytical methods. AI techniques under consideration for reactive agents are approximate or anytime reasoning that can be implemented using Bayesian belief networks as in Guardian. Cognitive agents are traditional expert systems that can be implemented in ART-Ada to meet soft real-time requirements. During the initial design of cognitive agents, it is critical to consider the migration path that would allow initial deployment on ground-based workstations with eventual deployment on on-board processors. ART-Ada technology enables this migration while Lisp-based technologies make it difficult if not impossible. In addition to reactive and cognitive agents, a meta-level agent would be needed to coordinate multiple agents and to provide meta-level control

    Context-aware adaptation in DySCAS

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    DySCAS is a dynamically self-configuring middleware for automotive control systems. The addition of autonomic, context-aware dynamic configuration to automotive control systems brings a potential for a wide range of benefits in terms of robustness, flexibility, upgrading etc. However, the automotive systems represent a particularly challenging domain for the deployment of autonomics concepts, having a combination of real-time performance constraints, severe resource limitations, safety-critical aspects and cost pressures. For these reasons current systems are statically configured. This paper describes the dynamic run-time configuration aspects of DySCAS and focuses on the extent to which context-aware adaptation has been achieved in DySCAS, and the ways in which the various design and implementation challenges are met
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