Three protocols for gossip-based failure detection services in large-scale heterogeneous clusters are analyzed and compared. The basic gossip protocol provides a means by which failures can be detected in large distri...
Three protocols for gossip-based failure detection services in large-scale heterogeneous clusters are analyzed and compared. The basic gossip protocol provides a means by which failures can be detected in large distributed systems in an asynchronous manner without the limits associated with reliable multicasting for group communications. The hierarchical protocol leverages the underlying network topology to achieve faster failure detection. In addition to studying the effectiveness and efficiency of these two agreement protocols, we propose a third protocol that extends the hierarchical approach by piggybacking gossip information on application-generated messages. The protocols are simulated and evaluated with a fault-injection model for scalable distributed systems comprised of clusters of workstations connected by high-performance networks, such as the CPlant system at Sandia National Laboratories. The model supports permanent and transient node and link failures, with rates specified at simulation time, for processors functioning in a fail-silent fashion. Through high-fidelity, CAD-based modeling and simulation, we demonstrate the strengths and weaknesses of each approach in terms of agreement time, number of gossips, and overall scalability.
This paper discusses validation and verification of simulation models. The different approaches to deciding model validity are presented; how model validation and verification relate to the model development process a...
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This paper discusses validation and verification of simulation models. The different approaches to deciding model validity are presented; how model validation and verification relate to the model development process are discussed; various validation techniques are defined; conceptual model validity, model verification, operational validity, and data validity are described; ways to document results are given; and a recommended procedure is presented.
This paper describes the results of the working group investigating the issues of empirical studies for evolving systems. The groups found that there were many issues that were central to successful evolution and this...
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This paper describes the results of the working group investigating the issues of empirical studies for evolving systems. The groups found that there were many issues that were central to successful evolution and this concluded that this is a very important area within software engineering. Finally nine main areas were selected for consideration. For each of these areas the central issues were identified as well as success factors. In some cases success stories were also described and the critical factors accounting for the success analyzed. In some cases it was later found that a number of areas were so tightly coupled that it was important to discuss them together.
A novel Aggressive Parameter Extraction (APE) algorithm is presented. Our APE algorithm addresses the optimal selection of parameter perturbations used to increase trust in parameter extraction uniqueness. We establis...
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A novel Aggressive Parameter Extraction (APE) algorithm is presented. Our APE algorithm addresses the optimal selection of parameter perturbations used to increase trust in parameter extraction uniqueness. We establish an appropriate criterion for the generation of these perturbations. The APE algorithm classifies possible solutions for the parameter extraction problem. Two different approaches for obtaining subsequent perturbations are utilized based on a classification of the extracted parameters. The APE algorithm is successfully demonstrated in parameter extraction of an HTS filter model.
Three useful modeling techniques for specifying discrete event simulation models are discussed. Hierarchical model specification provides for model specification at different levels of abstraction. Scaling of model el...
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Three useful modeling techniques for specifying discrete event simulation models are discussed. Hierarchical model specification provides for model specification at different levels of abstraction. Scaling of model elements provides for the combination of similarly structured and parallel operating model elements into arrays of both fixed and dynamic sizes. Reuse of model elements allows for the repeated use of model element specifications. The Hierarchical Control Flow Graph Model paradigm is used to demonstrate the techniques discussed.
We present a novel approach to microwave circuit modeling, space derivative mapping (SDM). SDM assumes the existence of an empirical model of the structure under consideration. It enables the construction of a space m...
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We present a novel approach to microwave circuit modeling, space derivative mapping (SDM). SDM assumes the existence of an empirical model of the structure under consideration. It enables the construction of a space mapping-based locally valid model exploiting, for the first time, both the empirical simulations and the response sensitivity information. Parameter extraction uniqueness is no longer important. Statistical analysis of microwave circuits illustrates the SDM technique.
We present a novel, hybrid aggressive space mapping (HASM) optimization algorithm. HASM is a hybrid approach exploiting both the trust region aggressive space mapping (TRASM) algorithm and direct optimization. It does...
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We present a novel, hybrid aggressive space mapping (HASM) optimization algorithm. HASM is a hybrid approach exploiting both the trust region aggressive space mapping (TRASM) algorithm and direct optimization. It does not assume that the final space-mapped design is the true optimal design and is robust against severe misalignment between the coarse and the fine models. The algorithm is based on a novel lemma that enables smooth switching from the TRASM optimization to direct optimization and vice versa. The new algorithm has been tested on several microwave filters and transformers.
A novel, comprehensive framework to engineering device modeling called Generalized Space Mapping (GSM) is introduced. The accuracy of available empirical models of microwave devices can be significantly enhanced by ex...
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A novel, comprehensive framework to engineering device modeling called Generalized Space Mapping (GSM) is introduced. The accuracy of available empirical models of microwave devices can be significantly enhanced by exploiting GSM. We present three fundamental illustrations: a basic Space Mapping Super Model (SMSM), a basic Frequency-Space Mapping Super Model (FSMSM) and Multiple Space Mapping (MSM). The new concept is verified on several device modeling problems, typically utilizing very few full-wave EM simulations, yielding remarkable improvement in accuracy.
A virtual reality modeling language (VRML) based application has been developed as a marketing tool for a commercial park. VRML is a new Web based technology for specifying and delivering three-dimensional interactive...
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A virtual reality modeling language (VRML) based application has been developed as a marketing tool for a commercial park. VRML is a new Web based technology for specifying and delivering three-dimensional interactive visualizations over the Internet through a Web browser. As a part of its definition, VRML includes primitives that specify geometries, sense different conditions in in the visualization, and allow custom definition of methods. Geometries and conditions may be linked so that the geometries can be modified or added interactively. The visualization features simple operation, an extensive menu structure, dynamic creation of objects, and an arbitration scheme.
Space mapping (SM) technology based neuromodels decrease the cost of training, improve generalization ability and reduce the complexity of the ANN topology w.r.t. classical neuromodeling. Three novel techniques are pr...
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Space mapping (SM) technology based neuromodels decrease the cost of training, improve generalization ability and reduce the complexity of the ANN topology w.r.t. classical neuromodeling. Three novel techniques are proposed to generate SM based neuromodels: space-mapped neuromodeling (SMN), frequency dependent space-mapped neuromodeling (FDSMN), and frequency-space-mapped neuromodeling (FSMN). Huber optimization is proposed to train the neuro-space-mapping (NSM). The techniques are illustrated by a microstrip right angle bend.
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