Complex Grid Computing

This article investigates the performance of grid computing systems whose interconnections are given by random and scale-free complex network models. Regular networks, which are common in parallel computing architectures, are also used as a standard for comparison. The processing load is assigned to the processing nodes on demand, and the efficiency of the overall computing is quantified in terms of the respective speed-ups. It is found that random networks allow higher computing efficiency than their scale-free counterparts as a consequence of the smaller number of isolated clusters implied by the former model. At the same time, for fixed cluster sizes, the scale free model tend to provide slightly better efficiency. Two modifications of the random and scale free paradigms, where new connections tend to favor more recently added nodes, are proposed and shown to be more effective for grid computing than the standard models. A well-defined correlation is observed between the topological properties of the network and their respective computing efficiency.Comment: 5 pages, 2 figure

Reference Frames and the Physical Gravito-Electromagnetic Analogy

The similarities between linearized gravity and electromagnetism are known since the early days of General Relativity. Using an exact approach based on tidal tensors, we show that such analogy holds only on very special conditions and depends crucially on the reference frame. This places restrictions on the validity of the "gravito-electromagnetic" equations commonly found in the literature.Comment: 9 Pages, 1 figure. To appear in the Proceedings of the IAU Symposium 261 "Relativity in Fundamental Astronomy: Dynamics, Reference Frames, and Data Analysis", Virginia Beach, USA, 27 April - 1 May 200

On the Efficiency of Data Representation on the Modeling and Characterization of Complex Networks

Specific choices about how to represent complex networks can have a substantial effect on the execution time required for the respective construction and analysis of those structures. In this work we report a comparison of the effects of representing complex networks statically as matrices or dynamically as spase structures. Three theoretical models of complex networks are considered: two types of Erdos-Renyi as well as the Barabasi-Albert model. We investigated the effect of the different representations with respect to the construction and measurement of several topological properties (i.e. degree, clustering coefficient, shortest path length, and betweenness centrality). We found that different forms of representation generally have a substantial effect on the execution time, with the sparse representation frequently resulting in remarkably superior performance

A topological analysis of a geographical model for internet

This paper presents the analysis of a complex networks model of Internet connectivity named “Geometric Growing Model with n\ud Redundant Edges” (GGM-RE-n). This approach models the growth of Internet while taking into account the physical position of the\ud nodes. The node degree distribution and average radius are investigated for different configurations of the networks. The results\ud provide insights about the progressive evolution of the networks as new edges are added, as well as about the effect of the locality\ud factor over the degree distribution and average radius.FAPESP (03/08269-7)FAPESP (05/00587-5)CNPq (301303/ 06-1

Predicting Efficiency in master-slave grid computing systems

This work reports a quantitative analysis to predicting the efficiency of distributed computing running in three models of complex networks: Barab\'asi-Albert, Erd\H{o}s-R\'enyi and Watts-Strogatz. A master/slave computing model is simulated. A node is selected as master and distributes tasks among the other nodes (the clients). Topological measurements associated with the master node (e.g. its degree or betwenness centrality) are extracted and considered as predictors of the total execution time. It is found that the closeness centrality provides the best alternative. The effect of network size was also investigated

On the effects of geographical constraints on task execution in complex networks

In the present work we investigate the effects of spatial constraints on the efficiency of task execution in systems underlain by geographical complex networks where the probability of connection decreases with the distance between the nodes. The investigation considers several configurations of the parameters defining the network connectivity, and the Barabasi-Albert network model is also considered for comparisons. The results show that the effect of connectivity is significant only for shorter tasks, that the locality of connections implied by the spatial constraints reduces efficency, and that the addition of edges can improve the efficiency of the execution, although with increasing locality of the connections the improvement is small

Caracterização da diversidade genética de linhagens comerciais de Coffea arabica através de marcadores moleculares do tipo RAPD, AFLP e SSR

A identificação de linhagens de Coffea arabica a partir de descritores botânicos e agronômicos é um problema para o desenvolvimento de cultivares. Basicamente, a limitada variação fenotípica observada em cultivares é o resultado de uma estreita variabilidade genética em C. arabica associada com uma origem genealógica próxima. Recentemente, os uso de marcadores moleculares tem contribuído para a caracterização e identificação de várias espécies de interesse comercial. O objetivo deste trabalho foi comparar a confiabilidade de três tipos de marcadores moleculares, RAPD, AFLP e SSR, para a caracterização da variabilidade genética e uma possível identificação de linhagens comerciais de Coffea desenvolvidas pelo IAC. Os métodos avaliados permitiram identificar polimorfismos entre cultivares. A variabilidade genética detectada por eles é muito semelhante, ainda que reduzida. Marcadores do tipo RAPD e SSR foram mais eficientes em análises de parentesco, e o agrupamento das linhagens correspondeu à sua origem genealógica. No entanto, nenhum dos métodos testados permitiu a identificação individual de linhagens. Neste caso, a utilização conjunta de descritores botânicos, agronômicos e marcadores moleculares é recomendada para a identificação precisa de linhagens, visando processos de proteção legal de cultivares de Coffea.One of the greatest problems in Coffea arabica breeding is identifying precisely any inbred line, based only on botanical and agronomical descriptors, because of the reduced genetic variability of the species, close pedigree origin, which results in small phenotypic variation. Recently, molecular markers have been used for plant germplasm characterization and identification in several commercial species. This work evaluates the reliability of three marker systems: RAPD, AFLP and SSR, to characterize the genetic variability of commercially-used Coffea inbred lines developed by the Instituto Agronômico (IAC), and their potential for cultivar identification. All methods identified polymorphisms among the cultivars. The genetic diversity recognized by the methods is very similar, although is very narrow. RAPD and SSR marker systems grouped more efficiently the evaluated cultivars according to parental origin. None of the methods allowed inbred line identification. Therefore for varietal protection, it would be necessary using a combination of botanical, agronomical and molecular markers descriptors for precise cultivar identification