Harmony: Towards automated self-adaptive consistency in cloud storage

In just a few years cloud computing has become a very popular paradigm and a business success story, with storage being one of the key features. To achieve high data availability, cloud storage services rely on replication. In this context, one major challenge is data consistency. In contrast to traditional approaches that are mostly based on strong consistency, many cloud storage services opt for weaker consistency models in order to achieve better availability and performance. This comes at the cost of a high probability of stale data being read, as the replicas involved in the reads may not always have the most recent write. In this paper, we propose a novel approach, named Harmony, which adaptively tunes the consistency level at run-time according to the application requirements. The key idea behind Harmony is an intelligent estimation model of stale reads, allowing to elastically scale up or down the number of replicas involved in read operations to maintain a low (possibly zero) tolerable fraction of stale reads. As a result, Harmony can meet the desired consistency of the applications while achieving good performance. We have implemented Harmony and performed extensive evaluations with the Cassandra cloud storage on Grid?5000 testbed and on Amazon EC2. The results show that Harmony can achieve good performance without exceeding the tolerated number of stale reads. For instance, in contrast to the static eventual consistency used in Cassandra, Harmony reduces the stale data being read by almost 80% while adding only minimal latency. Meanwhile, it improves the throughput of the system by 45% while maintaining the desired consistency requirements of the applications when compared to the strong consistency model in Cassandra.

Evaluación cuantitativa de pérdidas por peligros geológicos. Caso del archipiélago de Canarias: Inundaciones, sismicidad y vulcanismo

Existe una creciente preocupación por las catástrofes de origen natural que están por llegar, motivo por el que se están realizando estudios desde prácticamente todas las ramas de la ciencia. La razón para ello se puede encontrar en el miedo a que los eventos futuros puedan dificultar las actividades humanas, aunque no es el único factor. Por todo ello, se produce una dispersión muy importante incluso en los conceptos más elementales como qué debe ser considerado o cómo debe llamarse y catalogarse uno u otro elemento. En consecuencia, los métodos para comprender los riesgos naturales también son muy diferentes, rara vez encontrándose enfoques realmente multidisciplinares. Se han realizado algunos esfuerzos para crear un marco de entendimiento común como por ejemplo, la "Directiva sobre inundaciones" o, más recientemente, la Directiva Inspire. Las entidades aseguradoras y reaseguradoras son un actor importante entre los muchos involucrados en los estudios de riesgos. Su interés radica en el hecho de que terminan pagando la mayor parte de la factura, si no toda. Pero, a cuánto puede ascender esa factura, no es una pregunta fácil de responder aún en casos muy concretos, y sin embargo, es la pregunta que constantemente se plantea por parte de los tomadores de decisiones a todos los niveles. Este documento resume las actividades de investigación que han llevado a cabo al objeto de sentar un marco de referencia, implementando de enfoques numéricos capaces de hacer frente a algunas de las cuestiones más relevantes que se encuentran en casi todos los estudios de riesgos naturales, ensayando conceptos de manera pragmática. Para ello, se escogió un lugar experimental de acuerdo a diferentes criterios, como la densidad de población, la facilidad de proporcionar los límites geográficos claros, la presencia de tres de los procesos geológicos más importantes (inundaciones, terremotos y vulcanismo) y la disponibilidad de datos. El modelo aquí propuesto aprovecha fuentes de datos muy diversas para evaluar los peligros naturales, poniendo de relieve la necesidad de un enfoque multidisciplinar y emplea un catálogo de datos único, unificado, independiente (no orientado), coherente y homogéneo para estimar el valor de las propiedades. Ahora bien, los datos se explotan de manera diferente según cada tipo de peligro, manteniendo sin variación los conceptos subyacentes. Durante esta investigación, se ha encontrado una gran brecha en la relación entre las pérdidas reales y las probabilidades del peligro, algo contrario a lo que se ha pensado que debía ser el comportamiento más probable de los riesgos naturales, demostrando que los estudios de riesgo tienen vida útil muy limitada. En parte debido ello, el modelo propuesto en este estudio es el de trabajar con escenarios, fijando una probabilidad de ocurrencia, lo que es contrario al modelo clásico de evaluar funciones continuas de riesgo. Otra razón para abordar la cuestión mediante escenarios es forzar al modelo para proporcionar unas cifras creíbles de daño máximo fijando cuestiones como la ubicación espacial de un evento y sus probabilidades, aportando una nueva visión del "peor escenario posible” de probabilidad conocida. ABSTRACT There is a growing concern about catastrophes of natural origin about to come hence many studies are being carried out from almost any science branch. Even though it is not the only one, fear for the upcoming events that might jeopardize any given human activity is the main motive. A forking effect is therefore heavily present even on the basic concepts of what is to be considered or how should it be named and catalogued; as a consequence, methods towards understanding natural risks also show great differences and a multidisciplinary approach has seldomly been followed. Some efforts were made to create a common understanding of such a matter, the “Floods Directive” or more recently the Inspire Directive, are a couple of examples. The insurance sector is an important actor among the many involved. Their interest relies on the fact that, eventually, they pay most of the bill if not all. But how much could that be is not an easy question to be answerd even in a very specific case, and it is almost always the question posed by decision makers at all levels. This document summarizes research activities that have being carried out in order to put some solid ground to be followed, implementing numerical approaches that are capable of coping with some of the most relevant issues found in almost all natural risk studies, testing concepts pragmatically. In order to do so, an experimental site was selected according to different criteria, such as population density, the ease of providing clear geographical boundaries, the presence of three of the most important geological processes (floods, earthquakes and volcanism) and data availability. The model herein proposed takes advantage of very diferent data sources in the assessment of hazard, pointing out how a multidisciplinary approach is needed, and uses only one unified, independent, consistent, homogeneous (non objective driven) source for assessing property value. Data is exploited differently according to each hazard type, but the underlying concepts remain the same. During this research, a deep detachment was found between actual loss and hazard chances, contrarily to what has been thought to be the most likely behaviour of natural hazards, proving that risk studies have a very limited lifespan. Partially because of such finding, the model in this study addresses scenarios with fixed probability of occurrence, as opposed to studying a continuous hazard function as usually proposed. Another reason for studying scenarios was to force the model to provide a reliable figure after a set of given parameters where fixed, such as the spatial location of an event and its chances, so the “worst case” of a given return period could be found.

Selecting crop models for decision making in wheat insurance

In crop insurance, the accuracy with which the insurer quantifies the actual risk is highly dependent on the availability on actual yield data. Crop models might be valuable tools to generate data on expected yields for risk assessment when no historical records are available. However, selecting a crop model for a specific objective, location and implementation scale is a difficult task. A look inside the different crop and soil modules to understand how outputs are obtained might facilitate model choice. The objectives of this paper were (i) to assess the usefulness of crop models to be used within a crop insurance analysis and design and (ii) to select the most suitable crop model for drought risk assessment in semi-arid regions in Spain. For that purpose first, a pre-selection of crop models simulating wheat yield under rainfed growing conditions at the field scale was made, and second, four selected models (Aquacrop, CERES- Wheat, CropSyst and WOFOST) were compared in terms of modelling approaches, process descriptions and model outputs. Outputs of the four models for the simulation of winter wheat growth are comparable when water is not limiting, but differences are larger when simulating yields under rainfed conditions. These differences in rainfed yields are mainly related to the dissimilar simulated soil water availability and the assumed linkages with dry matter formation. We concluded that for the simulation of winter wheat growth at field scale in such semi-arid conditions, CERES-Wheat and CropSyst are preferred. WOFOST is a satisfactory compromise between data availability and complexity when detail data on soil is limited. Aquacrop integrates physiological processes in some representative parameters, thus diminishing the number of input parameters, what is seen as an advantage when observed data is scarce. However, the high sensitivity of this model to low water availability limits its use in the region considered. Contrary to the use of ensembles of crop models, we endorse that efforts be concentrated on selecting or rebuilding a model that includes approaches that better describe the agronomic conditions of the regions in which they will be applied. The use of such complex methodologies as crop models is associated with numerous sources of uncertainty, although these models are the best tools available to get insight in these complex agronomic systems.

Soil water availability modulation over estimated relative yield losses in wheat (Triticum aestivum L.) due to ozone exposure

The approach developed by Fuhrer in 1995 to estimate wheat yield losses induced by ozone and modulated by the soil water content (SWC) was applied to the data on Catalonian wheat yields. The aim of our work was to apply this approach and adjust it to Mediterranean environmental conditions by means of the necessary corrections. The main objective pursued was to prove the importance of soil water availability in the estimation of relative wheat yield losses as a factor that modifies the effects of tropospheric ozone on wheat, and to develop the algorithms required for the estimation of relative yield losses, adapted to the Mediterranean environmental conditions. The results show that this is an easy way to estimate relative yield losses just using meteorological data, without using ozone fluxes, which are much more difficult to calculate. Soil water availability is very important as a modulating factor of the effects of ozone on wheat; when soil water availability decreases, almost twice the amount of accumulated exposure to ozone is required to induce the same percentage of yield loss as in years when soil water availability is high.

Simulating Data Journalism to Communicate Hydrological Information from Sensor Networks

Presenting relevant information via web-based user friendly interfac- es makes the information more accessible to the general public. This is especial- ly useful for sensor networks that monitor natural environments. Adequately communicating this type of information helps increase awareness about the limited availability of natural resources and promotes their better use with sus- tainable practices. In this paper, I suggest an approach to communicating this information to wide audiences based on simulating data journalism using artifi- cial intelligence techniques. I analyze this approach by describing a pioneer knowledge-based system called VSAIH, which looks for news in hydrological data from a national sensor network in Spain and creates news stories that gen- eral users can understand. VSAIH integrates artificial intelligence techniques, including a model-based data analyzer and a presentation planner. In the paper, I also describe characteristics of the hydrological national sensor network and the technical solutions applied by VSAIH to simulate data journalism.

Diffuse illuminance availability on horizontal and vertical surfaces at Madrid, Spain

The overall objective of this work is to provide diffuse illuminance availability at Madrid (Spain) through a statistical analysis of illuminance values corresponding to a long-term data series. The illuminance values are obtained from irradiance measurements by means of different empirical models for luminous efficacy. The values of diffuse illuminance on a horizontal and on vertical surfaces facing the four cardinal points are estimated and the different aspects related to daylight availability in an area with specific climatic conditions are analyzed. The experimental data consist of global and diffuse irradiance measurements on a horizontal surface provided by the National Meteorological Agency in Spain (AEMET) for Madrid. These data consist of hourly values measured in the period of 1980–2005. The statistical results derived correspond to a daylight typical year for the five surfaces considered. This information will be useful to building experts to estimate natural illumination availability when daylighting techniques are applied in building design with the main aim of electric energy savings.

Brain tissue segmentation on Diffusion Weighted Magnetic Resonance data

Introduction Diffusion weighted Imaging (DWI) techniques are able to measure, in vivo and non-invasively, the diffusivity of water molecules inside the human brain. DWI has been applied on cerebral ischemia, brain maturation, epilepsy, multiple sclerosis, etc. [1]. Nowadays, there is a very high availability of these images. DWI allows the identification of brain tissues, so its accurate segmentation is a common initial step for the referred applications. Materials and Methods We present a validation study on automated segmentation of DWI based on the Gaussian mixture and hidden Markov random field models. This methodology is widely solved with iterative conditional modes algorithm, but some studies suggest [2] that graph-cuts (GC) algorithms improve the results when initialization is not close to the final solution. We implemented a segmentation tool integrating ITK with a GC algorithm [3], and a validation software using fuzzy overlap measures [4]. Results Segmentation accuracy of each tool is tested against a gold-standard segmentation obtained from a T1 MPRAGE magnetic resonance image of the same subject, registered to the DWI space. The proposed software shows meaningful improvements by using the GC energy minimization approach on DTI and DSI (Diffusion Spectrum Imaging) data. Conclusions The brain tissues segmentation on DWI is a fundamental step on many applications. Accuracy and robustness improvements are achieved with the proposed software, with high impact on the application’s final result.

Estudio de las posibilidades de los datos abiertos enlazados (Linked Open Data) para la realización de mashups de ámbito geográfico.

La web ha sufrido una drástica transformación en los últimos años, debido principalmente a su popularización y a la enorme cantidad de información que alberga. Debido a estos factores se ha dado el salto de la denominada Web de Documentos, a la Web Semántica, donde toda la información está relacionada con otra. Las principales ventajas de la información enlazada estriban en la facilidad de reutilización, accesibilidad y disponibilidad para ser encontrada por el usuario. En este trabajo se pretende poner de manifiesto la utilidad de los datos enlazados aplicados al ámbito geográfico y mostrar como pueden ser empleados hoy en día. Para ello se han explotado datos enlazados de carácter espacial provenientes de diferentes fuentes, a través de servidores externos o endpoints SPARQL. Además de eso se ha trabajado con un servidor privado capaz de proporcionar información enlazada almacenada en un equipo personal. La explotación de información enlazada se ha implementado en una aplicación web en lenguaje JavaScript, tratando de abstraer totalmente al usuario del tratamiento de los datos a nivel interno de la aplicación. Esta aplicación cuenta además con algunos módulos y opciones capaces de interactuar con las consultas realizadas a los servidores, consiguiendo un entorno más intuitivo y agradable para el usuario. ABSTRACT: In recent years the web has suffered a drastic transformation because of the popularization and the huge amount of stored information. Due to these factors it has gone from Documents web to Semantic web, where the data are linked. The main advantages of Linked Data lie in the ease of his reuse, accessibility and availability to be located by users. The aim of this research is to highlight the usefulness of the geographic linked data and show how can be used at present time. To get this, the spatial linked data coming from several sources have been managed through external servers or also called endpoints. Besides, it has been worked with a private server able to provide linked data stored in a personal computer. The use of linked data has been implemented in a JavaScript web application, trying completely to abstract the internally data treatment of the application to make the user ignore it. This application has some modules and options that are able to interact with the queries made to the servers, getting a more intuitive and kind environment for users.

Optimizing the creation of base populations for aquaculture breeding programs using phenotypic and genomic data and its consequences on genetic progress

The success of an aquaculture breeding program critically depends on the way in which the base population of breeders is constructed since all the genetic variability for the traits included originally in the breeding goal as well as those to be included in the future is contained in the initial founders. Traditionally, base populations were created from a number of wild strains by sampling equal numbers from each strain. However, for some aquaculture species improved strains are already available and, therefore, mean phenotypic values for economically important traits can be used as a criterion to optimize the sampling when creating base populations. Also, the increasing availability of genome-wide genotype information in aquaculture species could help to refine the estimation of relationships within and between candidate strains and, thus, to optimize the percentage of individuals to be sampled from each strain. This study explores the advantages of using phenotypic and genome-wide information when constructing base populations for aquaculture breeding programs in terms of initial and subsequent trait performance and genetic diversity level. Results show that a compromise solution between diversity and performance can be found when creating base populations. Up to 6% higher levels of phenotypic performance can be achieved at the same level of global diversity in the base population by optimizing the selection of breeders instead of sampling equal numbers from each strain. The higher performance observed in the base population persisted during 10 generations of phenotypic selection applied in the subsequent breeding program.

Implications of data-intensive applications for next generation mobile networks

Lately, the mobile data market has moved into a growth stage triggered by two facts: affordability of mobile broadband, and availability of data-friendly devices. At this stage, market growth is no longer dependent on push strategies from suppliers; on the contrary, demand is now driving the market. However, it will not be easy for mobile operating companies to cope up with the demand to come in the near future. The infrastructure that is needed to support corresponding demand is far from completion. Operators are forced to make heavy investments to upgrade and expand their networks. To decide how to handle the present and upcoming demand, they need to identify and understand the characteristics of the scenarios they face. This is precisely the aim of this article, which provides figures on the consequences for mobile infrastructures of a generalised mobile media uptake. Data from the Spanish mobile deployment case have been used to arrive at practical figures and illustration of results, but the conclusions are easily extended to other countries and regions