Use Of Self-organization Research Articles

The self-configuration of nodes using RSSI in a dense wireless sensor network

Wireless sensor networks (WSNs) may be made of a large amount of small devices that are able to sense changes in the environment, and communicate these changes throughout the network. An example of a similar network is a photo voltaic (PV) power plant, where there is a sensor connected to each solar panel. The task of each sensor is to sense the output of the panel which is then sent to a central node for processing. As the network grows, it becomes impractical and even impossible to configure all these nodes manually. And so, the use of self-organization and auto-configuration algorithms becomes essential. In this paper, three algorithms are proposed that allow nodes in the network to automatically identify their closest neighbors, relative location in the network, and select which frequency channel to operate in. This is done using the value of the Received Signal Strength Indicator (RSSI) of the messages sent and received during the setup phase. The performance of these algorithms is tested by means of both simulations and testbed experiments. Results show that the error in the performance of the algorithms decreases as we increase the number of RSSI values used for decision making. Additionally, the number of nodes in the network affects the setup error. However, the value of the error is still acceptable even with a high number of nodes.

Self-Organization and Explanatory Pluralism: Avoiding the Snares of Reductionism in Developmental Science

Over the last 20 years, the concept of self-organization has played a central role in efforts to establish a relational metatheoretical approach to the study of development. Yet the notion of self-organization that predominates in scientific discussions today has undergone a conceptual narrowing relative to the broader use and interpretation of self-organization that characterized the biologically-oriented systems thinking of Weiss and von Bertalanffy and was grounded in Kant's teleological account of organisms as natural ends or purposes. In this article, the author discusses how our conceptual use of self-organization in developmental science has changed under the influence of nonlinear dynamical systems theory and how these changes could actually foster rather than discourage new forms of reductionism in our thinking about development.

Epitaxial Self‐Organization: from Surfaces to Magnetic Materials

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Epitaxial self-organization: from surfaces to magnetic materials

Self-organization of magnetic materials is an emerging and active field. An overview of the use of self-organization for magnetic purposes is given, with a view to illustrate aspects that cannot be covered by lithography. A first set of issues concerns the quantitative study of low-dimensional magnetic phenomena (1D and 0D). Such effects also occur in microstructured and lithographically-patterned materials but cannot be studied in these because of the complexity of such materials. This includes magnetic ordering, magnetic anisotropy and superparamagnetism. A second set of issues concerns the possibility to directly use self-organization in devices. Two sets of examples are given: first, how superparamagnetism can be fought by fabricating thick self-organized structures, and second, what new or improved functionalities can be expected from self-organized magnetic systems, like the tailoring of magnetic anisotropy or controlled dispersion of properties. To cite this article: O. Fruchart, C. R. Physique 6 (2005).

Morphology and photoluminescence of Ge islands grown on Si(001)

The use of self-organization of nanostructures during growth of materials having a high lattice mismatch e.g. Ge on Si offers new possibilities for device applications. The Ge layers were grown on Si(001) substrates by low pressure chemical vapour deposition. Island size statistics derived from the atomic force micrographs show a trimodal size distribution at high average Ge layer thicknesses, whereas at low Ge layer thicknesses only a narrow monomodal island size distribution exists. Transmission electron micrographs reveal the type of relaxation of the Ge islands and the shape of islands after being capped by a Si overlayer. A correspondence between the broadening of the spectral emission and the island morphology can be concluded from photoluminescence measurements. Multiple stacked island layers exhibit a significant increase of integral intensity in comparison with a single layer of islands, grown under equal conditions. A clear vertical correlation between island positions in different layers and a continuous enlargement of island size in upper layers is found on transmission electron micrographs of stacked island layers.

Self-organization in connectionist models: Associative memory, dissipative structures, and thermodynamic law

In the development of connectionist models it is popular to rely on the concept of self-organization and to employ analogies from thermodynamics. Here we review some aspects of self-organization and thermodynamic law. We conclude that they do, indeed, have much to offer the modeling of human action. However, we further conclude that connectionists have failed to exploit the full potential of the properties inherent in a thermodynamic model of self-organization. Their use of self-organization lacks the imperatives of physical theorists or biologists who have written extensively on the topic. The use of computational temperature as an ordering principle for associative memory is analyzed. The more common approach in connectionism, to seek order through cooling, has less potential to explain the emergence of new behavioral properties than an approach that seeks order through heating. Thermodynamics as a source of analogies is also seen as limiting and we question the value of analogy as a basis for a scientific endeavor. An appeal to the constructive role of the Second Law as it operates on open systems can account for important features of organized activity. In this view the Second Law does not offer analogies; it is a law that describes the causal basis of human action.