Plataforma Cloud para monitoreo remoto de sistemas fotovoltaicos aislados en el Ecuador

Los sistemas fotovoltaicos son fuentes emergentes de energías renovables que generan electricidad a partir de la radiación solar. El monitoreo de los sistemas fotovoltaicos aislados proporciona información necesaria que permite a sus propietarios mantener, operar y controlar estos sistemas, reduciendo los costes de operación y evitando indeseadas interrupciones en el suministro eléctrico de zonas aisladas. En este artículo, se propone el desarrollo de una plataforma para el monitoreo de sistemas fotovoltaicos aislados en el Ecuador con el objetivo fundamental de desarrollar una solución escalable, basada en el uso de software libre, en el empleo de sensores de bajo consumo y en el desarrollo de servicios web en la modalidad ‘Software as a Service’ (SaaS) para el procesamiento, gestión y publicación de información registrada y la creación de un innovador centro de control solar fotovoltaico en el Ecuador.

Introducing mobile edge computing capabilities through distributed 5G Cloud Enabled Small Cells

Current trends in broadband mobile networks are addressed towards the placement of different capabilities at the edge of the mobile network in a centralised way. On one hand, the split of the eNB between baseband processing units and remote radio headers makes it possible to process some of the protocols in centralised premises, likely with virtualised resources. On the other hand, mobile edge computing makes use of processing and storage capabilities close to the air interface in order to deploy optimised services with minimum delay. The confluence of both trends is a hot topic in the definition of future 5G networks. The full centralisation of both technologies in cloud data centres imposes stringent requirements to the fronthaul connections in terms of throughput and latency. Therefore, all those cells with limited network access would not be able to offer these types of services. This paper proposes a solution for these cases, based on the placement of processing and storage capabilities close to the remote units, which is especially well suited for the deployment of clusters of small cells. The proposed cloud-enabled small cells include a highly efficient microserver with a limited set of virtualised resources offered to the cluster of small cells. As a result, a light data centre is created and commonly used for deploying centralised eNB and mobile edge computing functionalities. The paper covers the proposed architecture, with special focus on the integration of both aspects, and possible scenarios of application.

Optimización de la ejecución de flujos de trabajos empresariales en infraestructuras cloud

En la actualidad, el uso del Cloud Computing se está incrementando y existen muchos proveedores que ofrecen servicios que hacen uso de esta tecnología. Uno de ellos es Amazon Web Services, que a través de su servicio Amazon EC2, nos ofrece diferentes tipos de instancias que podemos utilizar según nuestras necesidades. El modelo de negocio de AWS se basa en el pago por uso, es decir, solo realizamos el pago por el tiempo que se utilicen las instancias. En este trabajo se implementa en Amazon EC2, una aplicación cuyo objetivo es extraer de diferentes fuentes de información, los datos de las ventas realizadas por las editoriales y librerías de España. Estos datos son procesados, cargados en una base de datos y con ellos se generan reportes estadísticos, que ayudarán a los clientes a tomar mejores decisiones. Debido a que la aplicación procesa una gran cantidad de datos, se propone el desarrollo y validación de un modelo, que nos permita obtener una ejecución óptima en Amazon EC2. En este modelo se tienen en cuenta el tiempo de ejecución, el coste por uso y una métrica de coste/rendimiento. Adicionalmente, se utilizará la tecnología de contenedores Docker para llevar a cabo un caso específico del despliegue de la aplicación.

Cloud Computing to Automate Information Units

This article will address the main technical aspects that facilitate the use and growth of computer technology in the cloud, which go hand in hand with the emergence of more and better services on the Internet and technological development of the broadband. Finally, we know what is the impact that the cloud computing technologies in the automation of information units.

Dietopro.com: una nueva herramienta de gestión dietoterapéutica basada en la tecnología cloud computing

Introducción: Los softwares dietoterapéuticos constituyen actualmente una herramienta básica en el tratamiento dietético de pacientes, ya sea desde un punto de vista fisiológico y/o patológico. Las nuevas tecnologías y la investigación en este sentido, han favorecido la aparición de nuevas aplicaciones de gestión dietético-nutricional que facilitan la gestión de la empresa dietoterapéutica. Objetivos: Estudiar comparativamente las principales aplicaciones dietoterapéuticas existentes en el mercado para dar criterio a los usuarios profesionales de la dietética y nutrición en la selección de una de las principales herramientas para éstos. Resultados: Desde nuestro punto de vista, dietopro. com resulta, junto con otras de las aplicaciones dietoterapéuticas analizadas, una de las más completas para la gestión de la clínica nutricional. Conclusión: En función de la necesidad del usuario, éste dispone de diferentes softwares dietéticos donde elegir. Se concluye que la selección de una u otra, depende de las necesidades del profesional.

COMPRESSIVE QUANTIZATION FOR SCALABLE CLOUD RADIO ACCESS NETWORKS

With the proliferation of new mobile devices and applications, the demand for ubiquitous wireless services has increased dramatically in recent years. The explosive growth in the wireless traffic requires the wireless networks to be scalable so that they can be efficiently extended to meet the wireless communication demands. In a wireless network, the interference power typically grows with the number of devices without necessary coordination among them. On the other hand, large scale coordination is always difficult due to the low-bandwidth and high-latency interfaces between access points (APs) in traditional wireless networks. To address this challenge, cloud radio access network (C-RAN) has been proposed, where a pool of base band units (BBUs) are connected to the distributed remote radio heads (RRHs) via high bandwidth and low latency links (i.e., the front-haul) and are responsible for all the baseband processing. But the insufficient front-haul link capacity may limit the scale of C-RAN and prevent it from fully utilizing the benefits made possible by the centralized baseband processing. As a result, the front-haul link capacity becomes a bottleneck in the scalability of C-RAN. In this dissertation, we explore the scalable C-RAN in the effort of tackling this challenge. In the first aspect of this dissertation, we investigate the scalability issues in the existing wireless networks and propose a novel time-reversal (TR) based scalable wireless network in which the interference power is naturally mitigated by the focusing effects of TR communications without coordination among APs or terminal devices (TDs). Due to this nice feature, it is shown that the system can be easily extended to serve more TDs. Motivated by the nice properties of TR communications in providing scalable wireless networking solutions, in the second aspect of this dissertation, we apply the TR based communications to the C-RAN and discover the TR tunneling effects which alleviate the traffic load in the front-haul links caused by the increment of TDs. We further design waveforming schemes to optimize the downlink and uplink transmissions in the TR based C-RAN, which are shown to improve the downlink and uplink transmission accuracies. Consequently, the traffic load in the front-haul links is further alleviated by the reducing re-transmissions caused by transmission errors. Moreover, inspired by the TR-based C-RAN, we propose the compressive quantization scheme which applies to the uplink of multi-antenna C-RAN so that more antennas can be utilized with the limited front-haul capacity, which provide rich spatial diversity such that the massive TDs can be served more efficiently.

Continuous Quality Assurance and Optimisation in Cloud-Based Virtual Enterprises

Part 18: Optimization in Collaborative Networks

A Novel Framework for Virtual Organization Creation on Cloud

Part 12: Collaboration Platforms

Multi-sensor Cloud and Aerosol Retrieval Simulator and Its Applications

Executing a cloud or aerosol physical properties retrieval algorithm from controlled synthetic data is an important step in retrieval algorithm development. Synthetic data can help answer questions about the sensitivity and performance of the algorithm or aid in determining how an existing retrieval algorithm may perform with a planned sensor. Synthetic data can also help in solving issues that may have surfaced in the retrieval results. Synthetic data become very important when other validation methods, such as field campaigns,are of limited scope. These tend to be of relatively short duration and often are costly. Ground stations have limited spatial coverage whilesynthetic data can cover large spatial and temporal scales and a wide variety of conditions at a low cost. In this work I develop an advanced cloud and aerosol retrieval simulator for the MODIS instrument, also known as Multi-sensor Cloud and Aerosol Retrieval Simulator (MCARS). In a close collaboration with the modeling community I have seamlessly combined the GEOS-5 global climate model with the DISORT radiative transfer code, widely used by the remote sensing community, with the observations from the MODIS instrument to create the simulator. With the MCARS simulator it was then possible to solve the long standing issue with the MODIS aerosol optical depth retrievals that had a low bias for smoke aerosols. MODIS aerosol retrieval did not account for effects of humidity on smoke aerosols. The MCARS simulator also revealed an issue that has not been recognized previously, namely,the value of fine mode fraction could create a linear dependence between retrieved aerosol optical depth and land surface reflectance. MCARS provided the ability to examine aerosol retrievals against “ground truth” for hundreds of thousands of simultaneous samples for an area covered by only three AERONET ground stations. Findings from MCARS are already being used to improve the performance of operational MODIS aerosol properties retrieval algorithms. The modeling community will use the MCARS data to create new parameterizations for aerosol properties as a function of properties of the atmospheric column and gain the ability to correct any assimilated retrieval data that may display similar dependencies in comparisons with ground measurements.

Orchestrating New Markets Using Cloud Services

Part 5: Service Orientation in Collaborative Networks

Enterprise Collaboration Framework for Managing, Advancing and Unifying the Functionality of Multiple Cloud-Based Services with the Help of a Graph API

Part 5: Service Orientation in Collaborative Networks

Dendroecology of Drimys brasiliensis Miers (Winteraceae) in two Atlantic cloud forests in Paraná State, Southern Brazil.

2016

Investigations of Cloud Microphysical Response to Mixing Using Digital Holography

Cloud edge mixing plays an important role in the life cycle and development of clouds. Entrainment of subsaturated air affects the cloud at the microscale, altering the number density and size distribution of its droplets. The resulting effect is determined by two timescales: the time required for the mixing event to complete, and the time required for the droplets to adjust to their new environment. If mixing is rapid, evaporation of droplets is uniform and said to be homogeneous in nature. In contrast, slow mixing (compared to the adjustment timescale) results in the droplets adjusting to the transient state of the mixture, producing an inhomogeneous result. Studying this process in real clouds involves the use of airborne optical instruments capable of measuring clouds at the `single particle' level. Single particle resolution allows for direct measurement of the droplet size distribution. This is in contrast to other `bulk' methods (i.e. hot-wire probes, lidar, radar) which measure a higher order moment of the distribution and require assumptions about the distribution shape to compute a size distribution. The sampling strategy of current optical instruments requires them to integrate over a path tens to hundreds of meters to form a single size distribution. This is much larger than typical mixing scales (which can extend down to the order of centimeters), resulting in difficulties resolving mixing signatures. The Holodec is an optical particle instrument that uses digital holography to record discrete, local volumes of droplets. This method allows for statistically significant size distributions to be calculated for centimeter scale volumes, allowing for full resolution at the scales important to the mixing process. The hologram also records the three dimensional position of all particles within the volume, allowing for the spatial structure of the cloud volume to be studied. Both of these features represent a new and unique view into the mixing problem. In this dissertation, holographic data recorded during two different field projects is analyzed to study the mixing structure of cumulus clouds. Using Holodec data, it is shown that mixing at cloud top can produce regions of clear but humid air that can subside down along the edge of the cloud as a narrow shell, or advect down shear as a `humid halo'. This air is then entrained into the cloud at lower levels, producing mixing that appears to be very inhomogeneous. This inhomogeneous-like mixing is shown to be well correlated with regions containing elevated concentrations of large droplets. This is used to argue in favor of the hypothesis that dilution can lead to enhanced droplet growth rates. I also make observations on the microscale spatial structure of observed cloud volumes recorded by the Holodec.