Managing Packet Data (Sessions) in 3G Mobile Networks

Tällä hetkellä kolmannen sukupolven matkapuhelinjärjestelmät ovat siirtyneet kaupalliseen vaiheeseen. Universal Mobile Telecommunication System (UMTS) on eräs kolmannen sukupolven matkapuhelinjärjestelmä, jota tullaan käyttämään Euroopassa. Diplomityön päämääränä on tutkia, kuinka pakettivälitteistä tiedonsiirtoa hallitaan UMTS - verkoissa. Diplomityö antaa yleiskuvan toisen sukupolven matkapuhelinjärjestelmien datapalveluiden kehityksestä kolmannen sukupolven nopeisiin matkapuhelinjärjestelmiin. Pakettivälitteisen verkon verkkoarkkitehtuuri on esitetty sekä sen, diplomityön kannalta, tärkeimpien osien toiminnallisuus on selvitetty. Myös pakettipohjaisten datayhteyksien eli istuntojen muodostaminen ja vapauttaminen sekä aktiivisen yhteyden ominaisuuksien muokkaaminen on esitetty tässä diplomityössä. Yhteydenhallintaprotokolla, Session Management (SM), on yksi protokolla, joka osallistuu pakettidatayhteyden hallintaan. SM -protokolla on käsitelty työssä yksityiskohtaisesti. SM -protokollan SDL toteutus on esitetty diplomityön käytännönosassa

La Comunidad geospacial y el acceso a datos oceanográficos

Nowadays, Oceanographic and Geospatial communities are closely related worlds. The problem is that they follow parallel paths in data storage, distributions, modelling and data analyzing. This situation produces different data model implementations for the same features. While Geospatial information systems have 2 or 3 dimensions, the Oceanographic models uses multidimensional parameters like temperature, salinity, streams, ocean colour... This implies significant differences between data models of both communities, and leads to difficulties in dataset analysis for both sciences. These troubles affect directly to the Mediterranean Institute for Advanced Studies ( IMEDEA (CSIC-UIB)). Researchers from this Institute perform intensive processing with data from oceanographic facilities like CTDs, moorings, gliders… and geospatial data collected related to the integrated management of coastal zones. In this paper, we present an approach solution based on THREDDS (Thematic Real-time Environmental Distributed Data Services). THREDDS allows data access through the standard geospatial data protocol Web Coverage Service, inside the European project (European Coastal Sea Operational Observing and Forecasting system). The goal of ECOOP is to consolidate, integrate and further develop existing European coastal and regional seas operational observing and forecasting systems into an integrated pan- European system targeted at detecting environmental and climate changes

Distributed mining of molecular fragments

In real world applications sequential algorithms of data mining and data exploration are often unsuitable for datasets with enormous size, high-dimensionality and complex data structure. Grid computing promises unprecedented opportunities for unlimited computing and storage resources. In this context there is the necessity to develop high performance distributed data mining algorithms. However, the computational complexity of the problem and the large amount of data to be explored often make the design of large scale applications particularly challenging. In this paper we present the first distributed formulation of a frequent subgraph mining algorithm for discriminative fragments of molecular compounds. Two distributed approaches have been developed and compared on the well known National Cancer Institute’s HIV-screening dataset. We present experimental results on a small-scale computing environment.

The distributed work of local action: interaction amongst virtually collocated research teams

Existing research on synchronous remote working in CSCW has highlighted the troubles that can arise because actions at one site are (partially) unavailable to remote colleagues. Such ‘local action’ is routinely characterised as a nuisance, a distraction, subordinate and the like. This paper explores interconnections between ‘local action’ and ‘distributed work’ in the case of a research team virtually collocated through ‘MiMeG’. MiMeG is an e-Social Science tool that facilitates ‘distributed data sessions’ in which social scientists are able to remotely collaborate on the real-time analysis of video data. The data are visible and controllable in a shared workspace and participants are additionally connected via audio conferencing. The findings reveal that whilst the (partial) unavailability of local action is at times problematic, it is also used as a resource for coordinating work. The paper considers how local action is interactionally managed in distributed data sessions and concludes by outlining implications of the analysis for the design and study of technologies to support group-to-group collaboration.

Data stream mining in ubiquitous environments: state-of-the-art and current directions

In this article, we review the state-of-the-art techniques in mining data streams for mobile and ubiquitous environments. We start the review with a concise background of data stream processing, presenting the building blocks for mining data streams. In a wide range of applications, data streams are required to be processed on small ubiquitous devices like smartphones and sensor devices. Mobile and ubiquitous data mining target these applications with tailored techniques and approaches addressing scarcity of resources and mobility issues. Two categories can be identified for mobile and ubiquitous mining of streaming data: single-node and distributed. This survey will cover both categories. Mining mobile and ubiquitous data require algorithms with the ability to monitor and adapt the working conditions to the available computational resources. We identify the key characteristics of these algorithms and present illustrative applications. Distributed data stream mining in the mobile environment is then discussed, presenting the Pocket Data Mining framework. Mobility of users stimulates the adoption of context-awareness in this area of research. Context-awareness and collaboration are discussed in the Collaborative Data Stream Mining, where agents share knowledge to learn adaptive accurate models.

Pocket data mining - big data on small devices

Owing to continuous advances in the computational power of handheld devices like smartphones and tablet computers, it has become possible to perform Big Data operations including modern data mining processes onboard these small devices. A decade of research has proved the feasibility of what has been termed as Mobile Data Mining, with a focus on one mobile device running data mining processes. However, it is not before 2010 until the authors of this book initiated the Pocket Data Mining (PDM) project exploiting the seamless communication among handheld devices performing data analysis tasks that were infeasible until recently. PDM is the process of collaboratively extracting knowledge from distributed data streams in a mobile computing environment. This book provides the reader with an in-depth treatment on this emerging area of research. Details of techniques used and thorough experimental studies are given. More importantly and exclusive to this book, the authors provide detailed practical guide on the deployment of PDM in the mobile environment. An important extension to the basic implementation of PDM dealing with concept drift is also reported. In the era of Big Data, potential applications of paramount importance offered by PDM in a variety of domains including security, business and telemedicine are discussed.

Desenvolvimento e aplicação de um software cristalográfico com protocolo de acesso a um banco de dados distribuído

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Searching and retrieving in content-based repositories of formal mathematical knowledge

In this thesis, the author presents a query language for an RDF (Resource Description Framework) database and discusses its applications in the context of the HELM project (the Hypertextual Electronic Library of Mathematics). This language aims at meeting the main requirements coming from the RDF community. in particular it includes: a human readable textual syntax and a machine-processable XML (Extensible Markup Language) syntax both for queries and for query results, a rigorously exposed formal semantics, a graph-oriented RDF data access model capable of exploring an entire RDF graph (including both RDF Models and RDF Schemata), a full set of Boolean operators to compose the query constraints, fully customizable and highly structured query results having a 4-dimensional geometry, some constructions taken from ordinary programming languages that simplify the formulation of complex queries. The HELM project aims at integrating the modern tools for the automation of formal reasoning with the most recent electronic publishing technologies, in order create and maintain a hypertextual, distributed virtual library of formal mathematical knowledge. In the spirit of the Semantic Web, the documents of this library include RDF metadata describing their structure and content in a machine-understandable form. Using the author's query engine, HELM exploits this information to implement some functionalities allowing the interactive and automatic retrieval of documents on the basis of content-aware requests that take into account the mathematical nature of these documents.

An autonomic framework for enhancing the quality of data grid services

Data grid services have been used to deal with the increasing needs of applications in terms of data volume and throughput. The large scale, heterogeneity and dynamism of grid environments often make management and tuning of these data services very complex. Furthermore, current high-performance I/O approaches are characterized by their high complexity and specific features that usually require specialized administrator skills. Autonomic computing can help manage this complexity. The present paper describes an autonomic subsystem intended to provide self-management features aimed at efficiently reducing the I/O problem in a grid environment, thereby enhancing the quality of service (QoS) of data access and storage services in the grid. Our proposal takes into account that data produced in an I/O system is not usually immediately required. Therefore, performance improvements are related not only to current but also to any future I/O access, as the actual data access usually occurs later on. Nevertheless, the exact time of the next I/O operations is unknown. Thus, our approach proposes a long-term prediction designed to forecast the future workload of grid components. This enables the autonomic subsystem to determine the optimal data placement to improve both current and future I/O operations.

Combining data mining and ontology engineering to enrich ontologies and linked data

In this position paper, we claim that the need for time consuming data preparation and result interpretation tasks in knowledge discovery, as well as for costly expert consultation and consensus building activities required for ontology building can be reduced through exploiting the interplay of data mining and ontology engineering. The aim is to obtain in a semi-automatic way new knowledge from distributed data sources that can be used for inference and reasoning, as well as to guide the extraction of further knowledge from these data sources. The proposed approach is based on the creation of a novel knowledge discovery method relying on the combination, through an iterative ?feedbackloop?, of (a) data mining techniques to make emerge implicit models from data and (b) pattern-based ontology engineering to capture these models in reusable, conceptual and inferable artefacts.

An Internet of Things approach for managing smart services provided by wearable devices.

The Internet of Things (IoT) is growing at a fast pace with new devices getting connected all the time. A new emerging group of these devices are the wearable devices, and Wireless Sensor Networks are a good way to integrate them in the IoT concept and bring new experiences to the daily life activities. In this paper we present an everyday life application involving a WSN as the base of a novel context-awareness sports scenario where physiological parameters are measured and sent to the WSN by wearable devices. Applications with several hardware components introduce the problem of heterogeneity in the network. In order to integrate different hardware platforms and to introduce a service-oriented semantic middleware solution into a single application, we propose the use of an Enterprise Service Bus (ESB) as a bridge for guaranteeing interoperability and integration of the different environments, thus introducing a semantic added value needed in the world of IoT-based systems. This approach places all the data acquired (e.g., via Internet data access) at application developers disposal, opening the system to new user applications. The user can then access the data through a wide variety of devices (smartphones, tablets, computers) and Operating Systems (Android, iOS, Windows, Linux, etc.).

INDICIa: a new distributed clustering protocol

Many data streaming applications produces massive amounts of data that must be processed in a distributed fashion due to the resource limitation of a single machine. We propose a distributed data stream clustering protocol. Theoretical analysis shows preliminary results about the quality of discovered clustering. In addition, we present results about the ability to reduce the time complexity respect to the centralized approach.

Desarrollo de nueva funcionalidad e interfaz web y móvil para la API MappingAPI2

Vivimos en la era de la información y del internet, tenemos la necesidad cada vez mayor de conseguir y compartir la información que existe. Esta necesidad se da en todos los ámbitos existentes pero con más ahínco probablemente sea en el área de la medicina, razón por la cual se llevan a cabo muchas investigaciones de distinta índole, lo cual ha llevado a generar un cantidad inimaginable de información y esta su vez muy heterogénea, haciendo cada vez más difícil unificarla y sacar conocimiento o valor agregado. Por lo cual se han llevado a cabo distintas investigaciones para dar solución a este problema, quizás la más importante y con más crecimiento es la búsqueda a partir de modelos de ontologías mediante el uso de sistemas que puedan consultarla. Este trabajo de Fin de Master hace hincapié es la generación de las consultas para poder acceder a la información que se encuentra de manera distribuida en distintos sitios y de manera heterogénea, mediante el uso de una API que genera el código SPARQL necesario. La API que se uso fue creada por el grupo de informática biomédica. También se buscó una manera eficiente de publicar esta API para su futuro uso en el proyecto p-medicine, por lo cual se creó un servicio RESTful para permitir generar las consultas deseadas desde cualquier plataforma, haciendo en esto caso más accesible y universal. Se le dio también una interfaz WEB a la API que permitiera hacer uso de la misma de una manera más amigable para el usuario. ---ABSTRACT---We live in the age of information and Internet so we have the need to consult and share the info that exists. This need comes is in every scope of our lives, probably one of the more important is the medicine, because it is the knowledge area that treats diseases and it tries to extents the live of the human beings. For that reason there have been many different researches generating huge amounts of heterogeneous and distributed information around the globe and making the data more difficult to consult. Consequently there have been many researches to look for an answer about to solve the problem of searching heterogeneous and distributed data, perhaps the more important if the one that use ontological models. This work is about the generation of the query statement based on the mapping API created by the biomedical informatics group. At the same time the project looks for the best way to publish and make available the API for its use in the p-medicine project, for that reason a RESTful API was made to allow the generation of consults from within the platform, becoming much more accessible and universal available. A Web interface was also made to the API, to let access to the final user in a friendly