Reuso, composición y refactorización de servicios heterogéneos

El paradigma de Computación Orientada a Servicios (SOC), promueve el desarrollo de aplicaciones distribuidas en ambientes heterogéneos, que son construidas ensamblando o componiendo servicios reusables, que se publican a través de una red y se acceden mediante protocolos específicos. SOC ha sido ampliamente adoptado con la tecnología de Servicios Web. Existen diferentes estilos de Servicios Web que amplían las oportunidades de selección de soluciones, pero generan un desafío de evaluación y ajuste de servicios heterogéneos. Entre los estilos se encuentran los servicios SOAP (con descripciones WSDL) y los servicios RESTful (con múltiples lenguajes de descripción tal como WADL, OpenAPI, etc.). Para afrontar estos desafíos se definió un Metamodelo de Servicios Heterogéneos que permite la evaluación y composición de servicios. Además, el desarrollo de servicios para reuso afronta la necesidad de reducir la complejidad de los servicios que afecta su comprensión e interoperabilidad. Para ello, se pueden utilizar métricas de complejidad de servicios y realizar refactorizaciones hasta alcanzar la complejidad deseada. Estos desafíos también son posibles por medio del Metamodelo de Servicios, para que un proveedor reajuste sus servicios y ofrezca nuevas soluciones en base a sus desarrollos previos.Eje: Ingeniería de Software.Red de Universidades con Carreras en Informátic

Edge-based Runtime Verification for the Internet of Things

Complex distributed systems such as the ones induced by Internet of Things (IoT) deployments, are expected to operate in compliance to their requirements. This can be checked by inspecting events flowing throughout the system, typically originating from end-devices and reflecting arbitrary actions, changes in state or sensing. Such events typically reflect the behavior of the overall IoT system – they may indicate executions which satisfy or violate its requirements. This article presents a service-based software architecture and technical framework supporting runtime verification for widely deployed, volatile IoT systems. At the lowest level, systems we consider are comprised of resource-constrained devices connected over wide area networks generating events. In our approach, monitors are deployed on edge components, receiving events originating from end-devices or other edge nodes. Temporal logic properties expressing desired requirements are then evaluated on each edge monitor in a runtime fashion. The system exhibits decentralization since evaluation occurs locally on edge nodes, and verdicts possibly affecting satisfaction of properties on other edge nodes are propagated accordingly. This reduces dependence on cloud infrastructures for IoT data collection and centralized processing. We illustrate how specification and runtime verification can be achieved in practice on a characteristic case study of smart parking. Finally, we demonstrate the feasibility of our design over a testbed instantiation, whereupon we evaluate performance and capacity limits of different hardware classes under monitoring workloads of varying intensity using state-of-the-art LPWAN technology

Human mobility: Models and applications

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this recordRecent years have witnessed an explosion of extensive geolocated datasets related to human movement, enabling scientists to quantitatively study individual and collective mobility patterns, and to generate models that can capture and reproduce the spatiotemporal structures and regularities in human trajectories. The study of human mobility is especially important for applications such as estimating migratory flows, traffic forecasting, urban planning, and epidemic modeling. In this survey, we review the approaches developed to reproduce various mobility patterns, with the main focus on recent developments. This review can be used both as an introduction to the fundamental modeling principles of human mobility, and as a collection of technical methods applicable to specific mobility-related problems. The review organizes the subject by differentiating between individual and population mobility and also between short-range and long-range mobility. Throughout the text the description of the theory is intertwined with real-world applications.US Army Research Offic

Human mobility:Models and applications

Recent years have witnessed an explosion of extensive geolocated datasets related to human movement, enabling scientists to quantitatively study individual and collective mobility patterns, and to generate models that can capture and reproduce the spatiotemporal structures and regularities in human trajectories. The study of human mobility is especially important for applications such as estimating migratory flows, traffic forecasting, urban planning, and epidemic modeling. In this survey, we review the approaches developed to reproduce various mobility patterns, with the main focus on recent developments. This review can be used both as an introduction to the fundamental modeling principles of human mobility, and as a collection of technical methods applicable to specific mobility-related problems. The review organizes the subject by differentiating between individual and population mobility and also between short-range and long-range mobility. Throughout the text the description of the theory is intertwined with real-world applications.Comment: 126 pages, 45+ figure

The Physics of Open Ended Evolution

abstract: What makes living systems different than non-living ones? Unfortunately this question is impossible to answer, at least currently. Instead, we must face computationally tangible questions based on our current understanding of physics, computation, information, and biology. Yet we have few insights into how living systems might quantifiably differ from their non-living counterparts, as in a mathematical foundation to explain away our observations of biological evolution, emergence, innovation, and organization. The development of a theory of living systems, if at all possible, demands a mathematical understanding of how data generated by complex biological systems changes over time. In addition, this theory ought to be broad enough as to not be constrained to an Earth-based biochemistry. In this dissertation, the philosophy of studying living systems from the perspective of traditional physics is first explored as a motivating discussion for subsequent research. Traditionally, we have often thought of the physical world from a bottom-up approach: things happening on a smaller scale aggregate into things happening on a larger scale. In addition, the laws of physics are generally considered static over time. Research suggests that biological evolution may follow dynamic laws that (at least in part) change as a function of the state of the system. Of the three featured research projects, cellular automata (CA) are used as a model to study certain aspects of living systems in two of them. These aspects include self-reference, open-ended evolution, local physical universality, subjectivity, and information processing. Open-ended evolution and local physical universality are attributed to the vast amount of innovation observed throughout biological evolution. Biological systems may distinguish themselves in terms of information processing and storage, not outside the theory of computation. The final research project concretely explores real-world phenomenon by means of mapping dominance hierarchies in the evolution of video game strategies. Though the main question of how life differs from non-life remains unanswered, the mechanisms behind open-ended evolution and physical universality are revealed.Dissertation/ThesisDoctoral Dissertation Physics 201

Knowledge Discovery through Mobility Data Integration

In the era of Big Data a huge amount of information are available from every sin- gle citizen of our hyper-connected world. A simple smartphone can collect data with different kinds of information: a big part of these are related to mobility. A smartphone is connected to networks, such as GSM, GPS, Internet (and then social networks): each of them can provide us information about where, how and why the user is moving across space and time. Data integration has a key role in this understanding process: the combination of different data sources increases the value of the extracted knowledge, even though such integration task is often not trivial. This thesis aim to represent a step toward a reliable Mobility Analysis framework, capable to exploit the richness of the spatio-temporal data nowadays available. The work done is an exploration of meaningful open challenges, from an efficient Map Matching of low sampling GPS data to Inferring Human Activities from GPS tracks. A further experimentation has been performed over GSM and Twitter data, in order to detect and recognize significant events in terms of people presence and related tweets. Another promising perspective is the use of such extracted knowledge to enrich actual geospatial Datasets with a ’Wisdom of the crowd’ dimension to derive, for instance, routing policies over road networks: most chosen paths among usual drivers are more meaningful than simple shortest paths

A review of machine learning applications in wildfire science and management

Artificial intelligence has been applied in wildfire science and management since the 1990s, with early applications including neural networks and expert systems. Since then the field has rapidly progressed congruently with the wide adoption of machine learning (ML) in the environmental sciences. Here, we present a scoping review of ML in wildfire science and management. Our objective is to improve awareness of ML among wildfire scientists and managers, as well as illustrate the challenging range of problems in wildfire science available to data scientists. We first present an overview of popular ML approaches used in wildfire science to date, and then review their use in wildfire science within six problem domains: 1) fuels characterization, fire detection, and mapping; 2) fire weather and climate change; 3) fire occurrence, susceptibility, and risk; 4) fire behavior prediction; 5) fire effects; and 6) fire management. We also discuss the advantages and limitations of various ML approaches and identify opportunities for future advances in wildfire science and management within a data science context. We identified 298 relevant publications, where the most frequently used ML methods included random forests, MaxEnt, artificial neural networks, decision trees, support vector machines, and genetic algorithms. There exists opportunities to apply more current ML methods (e.g., deep learning and agent based learning) in wildfire science. However, despite the ability of ML models to learn on their own, expertise in wildfire science is necessary to ensure realistic modelling of fire processes across multiple scales, while the complexity of some ML methods requires sophisticated knowledge for their application. Finally, we stress that the wildfire research and management community plays an active role in providing relevant, high quality data for use by practitioners of ML methods.Comment: 83 pages, 4 figures, 3 table

Speculations

From the Editorial Introduction: "Since I am convinced that nobody reads editorials I will keep my remarks brief. Putting together the inaugural issue of Speculations has been an unusual experience. It has depended on the collusion of fellow speculative types, the help of many anonymous reviewers, the endless patience of designer Thomas Gokey, and more hours than someone in the final year of their PhD should ever spend on a project. Looking over the final product I think it has all been worth it. This is the first journal dedicated to speculative realism and despite the obscurity of that term I think we all understand it as a handy label under which weird realists, continental metaphysicians, object oriented ontologists, transcendental realists, vitalists, and Lovecraftians can unite. This is also, perhaps, the first time a journal can boast that each contributor is also a blogger. This is the reason why Speculations could only ever be an online, open-access journal. …