International audienceWeb service orchestration is popular because the application logic is defined from a central and unique point of view, but it suffers from scalability issues. In choreography, the application is expressed as a direct communication between services without any central actor, making it scalable but also difficult to specify and implement. In this paper we present FOCAS, in which the application is described as a classic service orchestration extended by annotations expressing where activities, either atomic or composite, are to be executed. FOCAS analyzes the orchestration model and its distribution annotations and transforms the orchestration into a number of sub-orchestrations to be deployed on a set of distributed choreography servers, and then, deploys and executes the application. This approach seemingly fills the gap between "pure" orchestration (a single control server), and "pure" choreography (a server per service). The paper shows how FOCAS transforms a simple orchestration into a distributed one, fitting the distribution needs of the company, and also shows how choreography servers can be implemented using traditional orchestration engines
It is widely recognized that applications need to be remotely administrated. In general, application management and monitoring is supported by textual management consoles while graphical user interfaces specialized for their tasks are preferred from average users. Defining what must be monitored and what are the admin actions you want to perform on an application cannot be defined during the application development due to the fact that these needs evolve after the application deployment as we cannot completely predict the execution environment such as available devices. This paper presents an architecture and the corresponding infrastructure that allow administrators to define what they want to monitor and manage and automate the discovery and deployment of corresponding probes and related management console graphical plug-ins. This work has been validated on two different application domains.
Introducción: esta publicación es el producto de una investigación del grupo de investigación de computación avanzada y en gran escala (Cage) de la Universidad Industrial de Santander, a lo largo de 2018. Objetivo: Se propone un algoritmo de posicionamiento cooperativo en el que un conjunto de dispositivos intercambia observables satelitales, y estimaciones de distancia entre dispositivos GPS cercanos, con el objetivo de aumentar su precisión de posicionamiento. Metodología: se establecen escenarios donde los receptores de GPS intercambian información satelital, y utilizan diferentes modelos de corrección ionosférica con el fin de evaluar las condiciones en que es posible mejorar la precisión en posicionamiento. Conclusiones: El algoritmo propuesto produce una mayor precisión cuando todos los receptores emplean el mismo modelo de corrección ionosférica. Además, el nivel de incertidumbre en la medida de distancia entre dispositivos no presenta mayor influencia sobre la mejora de la precisión, cuando la separación entre receptores es muy grande. Originalidad: el algoritmo propuesto permite explotar la naturaleza del problema sin aumentar la complejidad a nivel de hardware y software, y se ofrece como una alternativa de solución de posicionamiento cooperativo de bajo costo. Limitación: Los resultados exponen la ejecución del algoritmo cooperativo utilizando archivos Rinex de estaciones de referencia gnss. Por lo tanto, para los escenarios en que la distancia de separación entre estaciones es muy alta, los niveles de error en posicionamiento pueden ser elevados.
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