3 resultados para Delay Tolerant Network

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP)


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The assessment of routing protocols for mobile wireless networks is a difficult task, because of the networks` dynamic behavior and the absence of benchmarks. However, some of these networks, such as intermittent wireless sensors networks, periodic or cyclic networks, and some delay tolerant networks (DTNs), have more predictable dynamics, as the temporal variations in the network topology can be considered as deterministic, which may make them easier to study. Recently, a graph theoretic model-the evolving graphs-was proposed to help capture the dynamic behavior of such networks, in view of the construction of least cost routing and other algorithms. The algorithms and insights obtained through this model are theoretically very efficient and intriguing. However, there is no study about the use of such theoretical results into practical situations. Therefore, the objective of our work is to analyze the applicability of the evolving graph theory in the construction of efficient routing protocols in realistic scenarios. In this paper, we use the NS2 network simulator to first implement an evolving graph based routing protocol, and then to use it as a benchmark when comparing the four major ad hoc routing protocols (AODV, DSR, OLSR and DSDV). Interestingly, our experiments show that evolving graphs have the potential to be an effective and powerful tool in the development and analysis of algorithms for dynamic networks, with predictable dynamics at least. In order to make this model widely applicable, however, some practical issues still have to be addressed and incorporated into the model, like adaptive algorithms. We also discuss such issues in this paper, as a result of our experience.

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Rationale: Major coronary vessels derive from the proepicardium, the cellular progenitor of the epicardium, coronary endothelium, and coronary smooth muscle cells (CoSMCs). CoSMCs are delayed in their differentiation relative to coronary endothelial cells (CoEs), such that CoSMCs mature only after CoEs have assembled into tubes. The mechanisms underlying this sequential CoE/CoSMC differentiation are unknown. Retinoic acid (RA) is crucial for vascular development and the main RA-synthesizing enzyme is progressively lost from epicardially derived cells as they differentiate into blood vessel types. In parallel, myocardial vascular endothelial growth factor (VEGF) expression also decreases along coronary vessel muscularization. Objective: We hypothesized that RA and VEGF act coordinately as physiological brakes to CoSMC differentiation. Methods and Results: In vitro assays (proepicardial cultures, cocultures, and RALDH2 [retinaldehyde dehydrogenase-2]/VEGF adenoviral overexpression) and in vivo inhibition of RA synthesis show that RA and VEGF act as repressors of CoSMC differentiation, whereas VEGF biases epicardially derived cell differentiation toward the endothelial phenotype. Conclusion: Experiments support a model in which early high levels of RA and VEGF prevent CoSMC differentiation from epicardially derived cells before RA and VEGF levels decline as an extensive endothelial network is established. We suggest this physiological delay guarantees the formation of a complex, hierarchical, tree of coronary vessels. (Circ Res. 2010;107:204-216.)

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This paper introduces a novel methodology to shape boundary characterization, where a shape is modeled into a small-world complex network. It uses degree and joint degree measurements in a dynamic evolution network to compose a set of shape descriptors. The proposed shape characterization method has all efficient power of shape characterization, it is robust, noise tolerant, scale invariant and rotation invariant. A leaf plant classification experiment is presented on three image databases in order to evaluate the method and compare it with other descriptors in the literature (Fourier descriptors, Curvature, Zernike moments and multiscale fractal dimension). (C) 2008 Elsevier Ltd. All rights reserved.