An online data access prediction and optimization approach for distributed systems

Current scientific applications have been producing large amounts of data. The processing, handling and analysis of such data require large-scale computing infrastructures such as clusters and grids. In this area, studies aim at improving the performance of data-intensive applications by optimizing data accesses. In order to achieve this goal, distributed storage systems have been considering techniques of data replication, migration, distribution, and access parallelism. However, the main drawback of those studies is that they do not take into account application behavior to perform data access optimization. This limitation motivated this paper which applies strategies to support the online prediction of application behavior in order to optimize data access operations on distributed systems, without requiring any information on past executions. In order to accomplish such a goal, this approach organizes application behaviors as time series and, then, analyzes and classifies those series according to their properties. By knowing properties, the approach selects modeling techniques to represent series and perform predictions, which are, later on, used to optimize data access operations. This new approach was implemented and evaluated using the OptorSim simulator, sponsored by the LHC-CERN project and widely employed by the scientific community. Experiments confirm this new approach reduces application execution time in about 50 percent, specially when handling large amounts of data.

Gaussian deconvolution: a useful method for a form-free modeling of scattering data from mono- and multilayered planar systems

A new method for analysis of scattering data from lamellar bilayer systems is presented. The method employs a form-free description of the cross-section structure of the bilayer and the fit is performed directly to the scattering data, introducing also a structure factor when required. The cross-section structure (electron density profile in the case of X-ray scattering) is described by a set of Gaussian functions and the technique is termed Gaussian deconvolution. The coefficients of the Gaussians are optimized using a constrained least-squares routine that induces smoothness of the electron density profile. The optimization is coupled with the point-of-inflection method for determining the optimal weight of the smoothness. With the new approach, it is possible to optimize simultaneously the form factor, structure factor and several other parameters in the model. The applicability of this method is demonstrated by using it in a study of a multilamellar system composed of lecithin bilayers, where the form factor and structure factor are obtained simultaneously, and the obtained results provided new insight into this very well known system.

Neural coding tools, based on Information Theory, applied to discrete time series: from electrophysiology to neuroethology

This work is supported by Brazilian agencies Fapesp, CAPES and CNPq

Connections between the Sznajd model with general confidence rules and graph theory

The Sznajd model is a sociophysics model that is used to model opinion propagation and consensus formation in societies. Its main feature is that its rules favor bigger groups of agreeing people. In a previous work, we generalized the bounded confidence rule in order to model biases and prejudices in discrete opinion models. In that work, we applied this modification to the Sznajd model and presented some preliminary results. The present work extends what we did in that paper. We present results linking many of the properties of the mean-field fixed points, with only a few qualitative aspects of the confidence rule (the biases and prejudices modeled), finding an interesting connection with graph theory problems. More precisely, we link the existence of fixed points with the notion of strongly connected graphs and the stability of fixed points with the problem of finding the maximal independent sets of a graph. We state these results and present comparisons between the mean field and simulations in Barabasi-Albert networks, followed by the main mathematical ideas and appendices with the rigorous proofs of our claims and some graph theory concepts, together with examples. We also show that there is no qualitative difference in the mean-field results if we require that a group of size q > 2, instead of a pair, of agreeing agents be formed before they attempt to convince other sites (for the mean field, this would coincide with the q-voter model).

Liberalism, Marxism and Democratic Theory Revisited: Proposal of a Joint Index of Political and Economic Democracy

Liberalism and Marxism are two schools of thought which have left deep imprints in sociological, political and economic theory. They are usually perceived as opposite, rival approaches. In the field of democracy there is a seemingly insurmountable rift around the question of political versus economic democracy. Liberals emphasize the former, Marxists the latter. Liberals say that economic democracy is too abstract and fuzzy a concept, therefore one should concentrate on the workings of an objective political democracy. Marxists insist that political democracy without economic democracy is insufficient. The article argues that both propositions are valid and not mutually exclusive. It proposes the creation of an operational, quantifiable index of economic democracy that can be used alongside the already existing indexes of political democracy. By using these two indexes jointly, political and economic democracy can be objectively evaluated. Thus, the requirements of both camps are met and maybe a more dialogical approach to democracy can be reached in the debate between liberals and Marxists. The joint index is used to evaluate the levels of economic and political democracy in the transition countries of Eastern Europe.

Uma arqueologia de diagramas cibernéticos

This paper investigates the use of explicit structures of information in architectural design. Particularly, it approaches the use of diagrams related to cybernetics and information theory in experimental practices in the 1960’s and 1970’s. It analyses the diagram of cybernetic control proposed by the cybernetician Gordon Pask for the Fun Palace, the diagrams produced by the utopian architect Yona Friedman in the conceptual description of the Flatwriter program and Christopher Alexander’s diagrams and his theories of Synthesis of Form and Pattern Language. Finally it establishes a brief parallel between current domestication and use of dataflow programming with the cybernetic diagrams, highlighting differences in their complexity approach.