Connectivity measures for internet topologies on the level of autonomous systems

Classical measures of network connectivity are the number of disjoint paths between a pair of nodes and the size of a minimum cut. For standard graphs, these measures can be computed efficiently using network flow techniques. However, in the Internet on the level of autonomous systems (ASs), referred to as AS-level Internet, routing policies impose restrictions on the paths that traffic can take in the network. These restrictions can be captured by the valley-free path model, which assumes a special directed graph model in which edge types represent relationships between ASs. We consider the adaptation of the classical connectivity measures to the valley-free path model, where it is -hard to compute them. Our first main contribution consists of presenting algorithms for the computation of disjoint paths, and minimum cuts, in the valley-free path model. These algorithms are useful for ASs that want to evaluate different options for selecting upstream providers to improve the robustness of their connection to the Internet. Our second main contribution is an experimental evaluation of our algorithms on four types of directed graph models of the AS-level Internet produced by different inference algorithms. Most importantly, the evaluation shows that our algorithms are able to compute optimal solutions to instances of realistic size of the connectivity problems in the valley-free path model in reasonable time. Furthermore, our experimental results provide information about the characteristics of the directed graph models of the AS-level Internet produced by different inference algorithms. It turns out that (i) we can quantify the difference between the undirected AS-level topology and the directed graph models with respect to fundamental connectivity measures, and (ii) the different inference algorithms yield topologies that are similar with respect to connectivity and are different with respect to the types of paths that exist between pairs of ASs.

Otimização do Uso das Águas da Barragem Santa Cruz-RN

The semiarid potiguar presents a quite discrepant. It is a region with one of the highest rates of artificial lake the world, but the policy of building dams to mitigate the problem of water scarcity does not solve, given that they have not demonstrated the ability to ensure supply human priority during periods of great drought and fail to solve the widespread demand existent in the semiarid. This work aims to present the optimal allocation of water, according to multiple uses and limited availability of water resources in the reservoir, from the simulation of the operation of the same, with the application of techniques to support decision making and performance evaluation alternatives for water use. The reservoir of Santa Cruz, the second largest reservoir of RN with storage capacity of approximately 600 million cubic meters, located about 20 km from the town of Apodi in RN, was conceived as a way to promote economic development in the region as well as the water supply of nearby towns. The techniques used are the simulation model of network flow ACQUANET and also the set of performance indicators. The results showed that the container has the capacity to serve up to 3,83m3/s flow required by existing uses, without any compromising the same. However, it was also observed that all anticipated future demands are implemented it will generate failures in meeting some uses

Excessive erythrocytosis compromises the blood-endothelium interface in erythropoietin-overexpressing mice

Elevated systemic haematocrit (Hct) increases risk of cardiovascular disorders, such as stroke and myocardial infarction. One possible pathophysiological mechanism could be a disturbance of the blood-endothelium interface. It has been shown that blood interacts with the endothelial surface via a thick hydrated macromolecular layer (the 'glycocalyx', or 'endothelial surface layer'--ESL), modulating various biological processes, including inflammation, permeability and atherosclerosis. However, the consequences of elevated Hct on the functional properties of this interface are incompletely understood. Thus, we combined intravital microscopy of an erythropoietin overexpressing transgenic mouse line (tg6) with excessive erythrocytosis (Hct 0.85), microviscometric analysis of haemodynamics, and a flow simulation model to assess the effects of elevated Hct on glycocalyx/ESL thickness and flow resistance. We show that the glycocalyx/ESL is nearly abolished in tg6 mice (thickness: wild-type control: 0.52 μm; tg6: 0.13 μm; P < 0.001). However, the corresponding reduction in network flow resistance contributes <20% to the maintenance of total peripheral resistance observed in tg6 mice. This suggests that the pathological effects of elevated Hct in these mice, and possibly also in polycythaemic humans, may relate to biological corollaries of a reduced ESL thickness and the consequent alteration in the blood-endothelium interface, rather than to an increase of flow resistance.

Scheduling the factory pick-up of new cars

Car manufacturers increasingly offer delivery programs for the factory pick-up of new cars. Such a program consists of a broad range of event-marketing activities. In this paper we investigate the problem of scheduling the delivery program activities of one day such that the sum of the customers’ waiting times is minimized. We show how to model this problem as a resource-constrained project scheduling problem with nonregular objective function, and we present a relaxation-based beam-search solution heuristic. The relaxations are solved by exploiting a duality relationship between temporal scheduling and min-cost network flow problems. This approach has been developed in cooperation with a German automaker. The performance of the heuristic has been evaluated based on practical and randomly generated test instances.

Pore water geochemistry of arctic deep sea sediments measured at station MSM16/2_809-1 (REF, Reference)

Pore water and turnover rates were determined for surface sediment cores obtained in 2009 and 2010. The pore water was extracted with Rhizons (Rhizon CSS: length 5 cm, pore diameter 0.15 µm; Rhizosphere Research Products, Wageningen, Netherlands) in 1 cm-resolution and immediately fixed in 5% zinc acetate (ZnAc) solution for sulfate, and sulfide analyses. The samples were diluted, filtered and the concentrations measured with non-suppressed anion exchange chromatography (Waters IC-Pak anion exchange column, waters 430 conductivity detector). The total sulfide concentrations (H2S + HS- + S**2-) were determined using the diamine complexation method (doi:10.4319/lo.1969.14.3.0454). Samples for dissolved inorganic carbon (DIC) and alkalinity measurements were preserved by adding 2 µl saturated mercury chloride (HgCl2) solution and stored headspace-free in gas-tight glass vials. DIC and alkalinity were measured using the flow injection method (detector VWR scientific model 1054) (doi:10.4319/lo.1992.37.5.1113). Dissolved sulfide was eliminated prior to the DIC measurement by adding 0.5 M molybdate solution (doi:10.4319/lo.1995.40.5.1011). Nutrient subsamples (10 - 15 ml) were stored at - 20 °C prior to concentration measurements with a Skalar Continuous-Flow Analyzer (doi:10.1002/9783527613984).

Column Generation Algorithms for Nonlinear Optimization II: Numerical Investigations

García et al. present a class of column generation (CG) algorithms for nonlinear programs. Its main motivation from a theoretical viewpoint is that under some circumstances, finite convergence can be achieved, in much the same way as for the classic simplicial decomposition method; the main practical motivation is that within the class there are certain nonlinear column generation problems that can accelerate the convergence of a solution approach which generates a sequence of feasible points. This algorithm can, for example, accelerate simplicial decomposition schemes by making the subproblems nonlinear. This paper complements the theoretical study on the asymptotic and finite convergence of these methods given in [1] with an experimental study focused on their computational efficiency. Three types of numerical experiments are conducted. The first group of test problems has been designed to study the parameters involved in these methods. The second group has been designed to investigate the role and the computation of the prolongation of the generated columns to the relative boundary. The last one has been designed to carry out a more complete investigation of the difference in computational efficiency between linear and nonlinear column generation approaches. In order to carry out this investigation, we consider two types of test problems: the first one is the nonlinear, capacitated single-commodity network flow problem of which several large-scale instances with varied degrees of nonlinearity and total capacity are constructed and investigated, and the second one is a combined traffic assignment model

Multiple paths extraction in images using a constrained expanded trellis

Single shortest path extraction algorithms have been used in a number of areas such as network flow and image analysis. In image analysis, shortest path techniques can be used for object boundary detection, crack detection, or stereo disparity estimation. Sometimes one needs to find multiple paths as opposed to a single path in a network or an image where the paths must satisfy certain constraints. In this paper, we propose a new algorithm to extract multiple paths simultaneously within an image using a constrained expanded trellis (CET) for feature extraction and object segmentation. We also give a number of application examples for our multiple paths extraction algorithm.

Computer Networks Security Models - A New Approach for Denial-of-Services Attacks Mitigation

Computer networks are a critical factor for the performance of a modern company. Managing networks is as important as managing any other aspect of the company’s performance and security. There are many tools and appliances for monitoring the traffic and analyzing the network flow security. They use different approaches and rely on a variety of characteristics of the network flows. Network researchers are still working on a common approach for security baselining that might enable early watch alerts. This research focuses on the network security models, particularly the Denial-of-Services (DoS) attacks mitigation, based on a network flow analysis using the flows measurements and the theory of Markov models. The content of the paper comprises the essentials of the author’s doctoral thesis.

Scaling and Multiscaling Exponents in Networks and Flows

The main focus of this paper is on mathematical theory and methods which have a direct bearing on problems involving multiscale phenomena. Modern technology is refining measurement and data collection to spatio-temporal scales on which observed geophysical phenomena are displayed as intrinsically highly variable and intermittant heirarchical structures,e.g. rainfall, turbulence, etc. The heirarchical structure is reflected in the occurence of a natural separation of scales which collectively manifest at some basic unit scale. Thus proper data analysis and inference require a mathematical framework which couples the variability over multiple decades of scale in which basic theoretical benchmarks can be identified and calculated. This continues the main theme of the research in this area of applied probability over the past twenty years.

Train scheduling in high speed railways: considering competitive effects

The railway planning problem is usually studied from two different points of view: macroscopic and microscopic. We propose a macroscopic approach for the high-speed rail scheduling problem where competitive effects are introduced. We study train frequency planning, timetable planning and rolling stock assignment problems and model the problem as a multi-commodity network flow problem considering competitive transport markets. The aim of the presented model is to maximize the total operator profit. We solve the optimization model using realistic probleminstances obtained from the network of the Spanish railwa operator RENFE, including other transport modes in Spain

Reduced Cerebral Blood Flow Within the Default-Mode Network and Within Total Gray Matter in Major Depression

The default-mode network (DMN) was shown to have aberrant blood oxygenation-level-dependent (BOLD) activity in major depressive disorder (MDD). While BOLD is a relative measure of neural activity, cerebral blood flow (CBF) is an absolute measure. Resting-state CBF alterations have been reported in MDD. However, the association of baseline CBF and CBF fluctuations is unclear in MDD. Therefore, the aim was to investigate the CBF within the DMN in MDD, applying a strictly data-driven approach. In 22 MDD patients and 22 matched healthy controls, CBF was acquired using arterial spin labeling (ASL) at rest. A concatenated independent component analysis was performed to identify the DMN within the ASL data. The perfusion of the DMN and its nodes was quantified and compared between groups. The DMN was identified in both groups with high spatial similarity. Absolute CBF values within the DMN were reduced in MDD patients (p<0.001). However, after controlling for whole-brain gray matter CBF and age, the group difference vanished. In patients, depression severity was correlated with reduced perfusion in the DMN in the posterior cingulate cortex and the right inferior parietal lobe. Hypoperfusion within the DMN in MDD is not specific to the DMN. Still, depression severity was linked to DMN node perfusion, supporting a role of the DMN in depression pathobiology. The finding has implications for the interpretation of BOLD functional magnetic resonance imaging data in MDD.