A Negotiation Style Recommender Based on Computational Ecology in Open Negotiation Environments

The system described herein represents the first example of a recommender system in digital ecosystems where agents negotiate services on behalf of small companies. The small companies compete not only with price or quality, but with a wider service-by-service composition by subcontracting with other companies. The final result of these offerings depends on negotiations at the scale of millions of small companies. This scale requires new platforms for supporting digital business ecosystems, as well as related services like open-id, trust management, monitors and recommenders. This is done in the Open Negotiation Environment (ONE), which is an open-source platform that allows agents, on behalf of small companies, to negotiate and use the ecosystem services, and enables the development of new agent technologies. The methods and tools of cyber engineering are necessary to build up Open Negotiation Environments that are stable, a basic condition for predictable business and reliable business environments. Aiming to build stable digital business ecosystems by means of improved collective intelligence, we introduce a model of negotiation style dynamics from the point of view of computational ecology. This model inspires an ecosystem monitor as well as a novel negotiation style recommender. The ecosystem monitor provides hints to the negotiation style recommender to achieve greater stability of an open negotiation environment in a digital business ecosystem. The greater stability provides the small companies with higher predictability, and therefore better business results. The negotiation style recommender is implemented with a simulated annealing algorithm at a constant temperature, and its impact is shown by applying it to a real case of an open negotiation environment populated by Italian companies

Integración de la recomendación WMS-C en los estándares preexistentes en la IDE

La experiencia en el uso de los servicios de mapas basados en la especificación Web Map Service (WMS) del Open Geospatial Consortium (OGC) ha demostrado que es necesario utilizar cachés de teselas para lograr un rendimiento aceptable en aplicaciones de difusión masiva, sin embargo no hay ningún mecanismo estándar para que los clientes de mapas aprovechen, a partir de la información proporcionada por el servidor de mapas, la disponibilidad de esta caché. A la espera de que la nueva recomendación WMTS se implante suficientemente, el mecanismo más extendido es la recomendación de perfil WMS-C de OsGeo. Para conseguir que la definición de mapas que contienen servicios WMSC sea lo más automática posible, se ha ampliado el servidor Geoserver para soportar un modelo de mapas de acuerdo con la recomendación WMC con algunas extensiones ad-hoc. La extensión desarrollada para Geoserver amplía su API REST para incluir soporte de WMC. De esta forma, cuando se registra una nueva configuración de mapa, mediante un documento WMC, en el que ciertas capas están cacheadas se procede automáticamente a la activación del cacheado mediante la extensión GeoWebCache. Para la utilización de las nuevas capacidades proporcionadas a Geoserver, se ha desarrollado un cliente de mapas que identifica la existencia de capas cacheadas y procede a utilizar, según convenga, los servicios cacheados y los servicios WMS tradicionales

Geoservicios web SIOSE: un sistema de información como servicio público

Tras finalizar la producción del Sistema de Información de Ocupación de Suelo en España (SIOSE) afrontamos su publicación en la red. A la hora de decidir la estrategia de difusión de la información debemos tener en cuenta las necesidades de los usuarios, dando acceso a la visualización, consulta y análisis de los datos originales del sistema y de sus diferentes vistas temáticas. SIOSE tiene, para realizar esta tarea de forma adecuada, dos características que nos condicionan: su gran volumen de información y la complejidad semántica de su modelo de datos orientado a objetos. A partir de una arquitectura construida con componentes de software libre, desde el sistema operativo hasta las aplicaciones servidoras; los geoservicios web estándar son la primera opción para comunicar información geográfica a través de la web, pero las posibles soluciones son múltiples y muy variadas. Además los servicios deben combinarse y coordinarse con otras herramientas de publicación, como la libre descarga de los datos en bruto, para conseguir que SIOSE cumpla con su función de infraestructura de información territorial sobre la que generar valor añadido y para que sea una herramienta útil de análisis del territorio. Describiremos como hemos configurado nuestros servicios de visualización y consulta de los datos para mostrar en la red toda la jerarquía de información y los diferentes enfoques de análisis con los que se puede abordar SIOSE y como hemos intentado optimizar el rendimiento de estos servicios para ofrecer tiempos de respuesta adecuados ante cualquier posible petición

Running Climate Models On The NERC Cluster Grid Using G-Rex

Compute grids are used widely in many areas of environmental science, but there has been limited uptake of grid computing by the climate modelling community, partly because the characteristics of many climate models make them difficult to use with popular grid middleware systems. In particular, climate models usually produce large volumes of output data, and running them usually involves complicated workflows implemented as shell scripts. For example, NEMO (Smith et al. 2008) is a state-of-the-art ocean model that is used currently for operational ocean forecasting in France, and will soon be used in the UK for both ocean forecasting and climate modelling. On a typical modern cluster, a particular one year global ocean simulation at 1-degree resolution takes about three hours when running on 40 processors, and produces roughly 20 GB of output as 50000 separate files. 50-year simulations are common, during which the model is resubmitted as a new job after each year. Running NEMO relies on a set of complicated shell scripts and command utilities for data pre-processing and post-processing prior to job resubmission. Grid Remote Execution (G-Rex) is a pure Java grid middleware system that allows scientific applications to be deployed as Web services on remote computer systems, and then launched and controlled as if they are running on the user's own computer. Although G-Rex is general purpose middleware it has two key features that make it particularly suitable for remote execution of climate models: (1) Output from the model is transferred back to the user while the run is in progress to prevent it from accumulating on the remote system and to allow the user to monitor the model; (2) The client component is a command-line program that can easily be incorporated into existing model work-flow scripts. G-Rex has a REST (Fielding, 2000) architectural style, which allows client programs to be very simple and lightweight and allows users to interact with model runs using only a basic HTTP client (such as a Web browser or the curl utility) if they wish. This design also allows for new client interfaces to be developed in other programming languages with relatively little effort. The G-Rex server is a standard Web application that runs inside a servlet container such as Apache Tomcat and is therefore easy to install and maintain by system administrators. G-Rex is employed as the middleware for the NERC1 Cluster Grid, a small grid of HPC2 clusters belonging to collaborating NERC research institutes. Currently the NEMO (Smith et al. 2008) and POLCOMS (Holt et al, 2008) ocean models are installed, and there are plans to install the Hadley Centre’s HadCM3 model for use in the decadal climate prediction project GCEP (Haines et al., 2008). The science projects involving NEMO on the Grid have a particular focus on data assimilation (Smith et al. 2008), a technique that involves constraining model simulations with observations. The POLCOMS model will play an important part in the GCOMS project (Holt et al, 2008), which aims to simulate the world’s coastal oceans. A typical use of G-Rex by a scientist to run a climate model on the NERC Cluster Grid proceeds as follows :(1) The scientist prepares input files on his or her local machine. (2) Using information provided by the Grid’s Ganglia3 monitoring system, the scientist selects an appropriate compute resource. (3) The scientist runs the relevant workflow script on his or her local machine. This is unmodified except that calls to run the model (e.g. with “mpirun”) are simply replaced with calls to "GRexRun" (4) The G-Rex middleware automatically handles the uploading of input files to the remote resource, and the downloading of output files back to the user, including their deletion from the remote system, during the run. (5) The scientist monitors the output files, using familiar analysis and visualization tools on his or her own local machine. G-Rex is well suited to climate modelling because it addresses many of the middleware usability issues that have led to limited uptake of grid computing by climate scientists. It is a lightweight, low-impact and easy-to-install solution that is currently designed for use in relatively small grids such as the NERC Cluster Grid. A current topic of research is the use of G-Rex as an easy-to-use front-end to larger-scale Grid resources such as the UK National Grid service.

An ECOOP web portal for visualising and comparing distributed coastal oceanography model and in situ data

As part of a large European coastal operational oceanography project (ECOOP), we have developed a web portal for the display and comparison of model and in situ marine data. The distributed model and in situ datasets are accessed via an Open Geospatial Consortium Web Map Service (WMS) and Web Feature Service (WFS) respectively. These services were developed independently and readily integrated for the purposes of the ECOOP project, illustrating the ease of interoperability resulting from adherence to international standards. The key feature of the portal is the ability to display co-plotted timeseries of the in situ and model data and the quantification of misfits between the two. By using standards-based web technology we allow the user to quickly and easily explore over twenty model data feeds and compare these with dozens of in situ data feeds without being concerned with the low level details of differing file formats or the physical location of the data. Scientific and operational benefits to this work include model validation, quality control of observations, data assimilation and decision support in near real time. In these areas it is essential to be able to bring different data streams together from often disparate locations.

Integrating the Climate Science Modelling Language with geospatial software and services

Much consideration is rightly given to the design of metadata models to describe data. At the other end of the data-delivery spectrum much thought has also been given to the design of geospatial delivery interfaces such as the Open Geospatial Consortium standards, Web Coverage Service (WCS), Web Map Server and Web Feature Service (WFS). Our recent experience with the Climate Science Modelling Language shows that an implementation gap exists where many challenges remain unsolved. To bridge this gap requires transposing information and data from one world view of geospatial climate data to another. Some of the issues include: the loss of information in mapping to a common information model, the need to create ‘views’ onto file-based storage, and the need to map onto an appropriate delivery interface (as with the choice between WFS and WCS for feature types with coverage-valued properties). Here we summarise the approaches we have taken in facing up to these problems.

Performance Analysis of a Semantics Enabled Service Registry

Service discovery is a critical task in service-oriented architectures such as the Grid and Web Services. In this paper, we study a semantics enabled service registry, GRIMOIRES, from a performance perspective. GRIMOIRES is designed to be the registry for myGrid and the OMII software distribution. We study the scalability of GRIMOIRES against the amount of information that has been published into it. The methodology we use and the data we present are helpful for researchers to understand the performance characteristics of the registry and, more generally, of semantics enabled service discovery. Based on this experimentation, we claim that GRIMOIRES is an efficient semantics-aware service discovery engine.

Performance Analysis of a Semantics Enabled Service Registry

Service discovery is a critical task in service-oriented architectures such as the Grid and Web Services. In this paper, we study a semantics enabled service registry, GRIMOIRES, from a performance perspective. GRIMOIRES is designed to be the registry for myGrid and the OMII software distribution. We study the scalability of GRIMOIRES against the amount of information that has been published into it. The methodology we use and the data we present are helpful for researchers to understand the performance characteristics of the registry and, more generally, of semantics enabled service discovery. Based on this experimentation, we claim that GRIMOIRES is an efficient semantics-aware service discovery engine.

Personalised Grid Service Discovery

The authors take a broad view that ultimately Grid- or Web-services must be located via personalised, semantic-rich discovery processes. They argue that such processes must rely on the storage of arbitrary metadata about services that originates from both service providers and service users. Examples of such metadata are reliability metrics, quality of service data, or semantic service description markup. This paper presents UDDI-MT, an extension to the standard UDDI service directory approach that supports the storage of such metadata via a tunnelling technique that ties the metadata store to the original UDDI directory. They also discuss the use of a rich, graph-based RDF query language for syntactic queries on this data. Finally, they analyse the performance of each of these contributions in our implementation.

Personalised Grid Service Discovery

We take a broad view that ultimately Grid- or Web-services must be located via personalised, semantic-rich discovery processes. We argue that such processes must rely on the storage of arbitrary metadata about services that originates from both service providers and service users. Examples of such metadata are reliability metrics, quality of service data, or semantic service description markup. This paper presents UDDI-MT, an extension to the standard UDDI service directory approach that supports the storage of such metadata via a tunnelling technique that ties the metadata store to the original UDDI directory. We also discuss the use of a rich, graph-based RDF query language for syntactic queries on this data. Finally, we analyse the performance of each of these contributions in our implementation.

Security Issues in a SOA-based Provenance System

Recent work has begun exploring the characterization and utilization of provenance in systems based on the Service Oriented Architecture (such as Web Services and Grid based environments). One of the salient issues related to provenance use within any given system is its security. In a broad sense, security requirements arise within any data archival and retrieval system, however provenance presents unique requirements of its own. These requirements are additionally dependent on the architectural and environmental context that a provenance system operates in. We seek to analyze the security considerations pertaining to a Service Oriented Architecture based provenance system. Towards this end, we describe the components of such a system and illustrate the security considerations that arise within it. Concurrently, we outline possible approaches to address them.

A Methodology for Building Service-Oriented Applications in the Presence of Non-Functional Properties

This thesis presents ⇡SOD-M (Policy-based Service Oriented Development Methodology), a methodology for modeling reliable service-based applications using policies. It proposes a model driven method with: (i) a set of meta-models for representing non-functional constraints associated to service-based applications, starting from an use case model until a service composition model; (ii) a platform providing guidelines for expressing the composition and the policies; (iii) model-to-model and model-to-text transformation rules for semi-automatizing the implementation of reliable service-based applications; and (iv) an environment that implements these meta-models and rules, and enables the application of ⇡SOD-M. This thesis also presents a classification and nomenclature for non-functional requirements for developing service-oriented applications. Our approach is intended to add value to the development of service-oriented applications that have quality requirements needs. This work uses concepts from the service-oriented development, non-functional requirements design and model-driven delevopment areas to propose a solution that minimizes the problem of reliable service modeling. Some examples are developed as proof of concepts

Cloud Integrator: uma plataforma para composição de serviços em ambientes de computação em nuvem

With the advance of the Cloud Computing paradigm, a single service offered by a cloud platform may not be enough to meet all the application requirements. To fulfill such requirements, it may be necessary, instead of a single service, a composition of services that aggregates services provided by different cloud platforms. In order to generate aggregated value for the user, this composition of services provided by several Cloud Computing platforms requires a solution in terms of platforms integration, which encompasses the manipulation of a wide number of noninteroperable APIs and protocols from different platform vendors. In this scenario, this work presents Cloud Integrator, a middleware platform for composing services provided by different Cloud Computing platforms. Besides providing an environment that facilitates the development and execution of applications that use such services, Cloud Integrator works as a mediator by providing mechanisms for building applications through composition and selection of semantic Web services that take into account metadata about the services, such as QoS (Quality of Service), prices, etc. Moreover, the proposed middleware platform provides an adaptation mechanism that can be triggered in case of failure or quality degradation of one or more services used by the running application in order to ensure its quality and availability. In this work, through a case study that consists of an application that use services provided by different cloud platforms, Cloud Integrator is evaluated in terms of the efficiency of the performed service composition, selection and adaptation processes, as well as the potential of using this middleware in heterogeneous computational clouds scenarios

Geração de processos WS-BPEL com base em um algoritmo de reescrita de regras

Web services are computational solutions designed according to the principles of Service Oriented Computing. Web services can be built upon pre-existing services available on the Internet by using composition languages. We propose a method to generate WS-BPEL processes from abstract specifications provided with high-level control-flow information. The proposed method allows the composition designer to concentrate on high-level specifi- cations, in order to increase productivity and generate specifications that are independent of specific web services. We consider service orchestrations, that is compositions where a central process coordinates all the operations of the application. The process of generating compositions is based on a rule rewriting algorithm, which has been extended to support basic control-flow information.We created a prototype of the extended refinement method and performed experiments over simple case studies