Comparison of Information Representation Formalisms for Scalable File Agnostic Information Infrastructures

In the early days of computing, files where just a natural way of storing information -- which reflected the way one would file their punch cards in a cabinet drawer. Unfortunately, the requirement to fragment information into such chunks, is a huge bottleneck for the evolution of global information space that the Internet has become. The concept of file causes several problems including unnatural clustering of information, unnecessary replication of data and very expensive information discovery in distributed computing environments. The overall goal of this work is to design an architecture enabling new era in computing and networking -- a computing infrastructure without the concept of file. Files are seen by many specialists as one of the main bottlenecks of modern IT systems evolution. This is mostly due to a very unnatural fragmentation of information into chunks which are easier to manage by operating systems but much more difficult for information processing tools and eventually by humans themselves

Integration of Heterogeneous Data Sources in an Ontological Knowledge Base

In this paper we present X2R, a system for integrating heterogeneous data sources in an ontological knowledge base. The main goal of the system is to create a unified view of information stored in relational, XML and LDAP data sources within an organization, expressed in RDF using a common ontology and valid according to a prescribed set of integrity constraints. X2R supports a wide range of source schemas and target ontologies by allowing the user to define potentially complex transformations of data between the original data source and the unified knowledge base. A rich set of integrity constraint primitives has been provided to ensure the quality of the unified data set. They are also leveraged in a novel approach towards semantic optimization of SPARQL queries

INTERACTIVE CLOUD DATA FARMING ENVIRONMENT FOR MILITARY MISSION PLANNING SUPPORT

In a modern globalised world, military and peace keeping forces often face situations which require very subtle and well planned operations taking into account cultural and social aspects of a given region and its population as well as dynamic psychological awareness related to recent events which can have impact on the attitude of the civilians. The goal of the EUSAS project is to develop a prototype of a system enabling mission planning support and training capabilities for soldiers and police forces dealing with asymmetric threat situations, such as crowd control in urban territory. In this paper, we discuss the data-farming infrastructure developed for this project, allowing generation of large amount of data from agent based simulations for further analysis allowing soldier training and evaluation of possible outcomes of different rules of engagement

FiVO/QStorMan Semantic Toolkit for Supporting Data-Intensive Applications in Distributed Environments

In this paper we present a semantic-based approach for supporting data-intensive applications in distributed environments. The approach is characterized by usage of explicit definition of non-functional quality parameters regarding storage systems, semantic descriptions of the available storage infrastructre and monitoring data concering the infrastructure workload and users operation, along with an implementation of the approach in the form of a toolkit called FiVO/QStorMan. In particular, we describe semantic descriptions, which are exploited in the storage resource provisioning process. In addition, the paper describes results of the performed experimental evaluation of the toolkit, which confirm the effectiveness of the proposed approach for the storage resource provisioning

A Toolkit For Storage Qos Provisioning For Data-Intensive Applications

This paper describes a programming toolkit developed in the PL-Grid project, named QStorMan, which supports storage QoS provisioning for data-intensive applications in distributed environments. QStorMan exploits knowledge-oriented methods for matching storage resources to non-functional requirements, which are defined for a data-intensive application. In order to support various usage scenarios, QStorMan provides two interfaces, such as programming libraries or a web portal. The interfaces allow to define the requirements either directly in an application source code or by using an intuitive graphical interface. The first way provides finer granularity, e.g., each portion of data processed by an application can define a different set of requirements. The second method is aimed at legacy applications support, which source code can not be modified. The toolkit has been evaluated using synthetic benchmarks and the production infrastructure of PL-Grid, in particular its storage infrastructure, which utilizes the Lustre file system

Privacy Aware On-Demand Resource Provisioning for IoT Data Processing

International audienceEdge processing in IoT networks offers the ability to enforce privacy at the point of data collection. However, such enforcement requires extra processing in terms of data filtering and the ability to configure the device with knowledge of policy. Supporting this processing with Cloud resources can reduce the burden this extra processing places on edge processing nodes and provide a route to enable user defined policy. To enable this work from the PaaSage project [12] into the Cloud modelling language is applied to IoT networks to enable standardised management of IoT and Cloud integration and enable edge processing to effectively use the Cloud in a privacy protecting way

Unified metadata management in large distributed computing infrastructures

Promotor: Jacek Kitowski, Renata Słota.Recenzent: Marian Wysocki, Bogdan Wiszniewski.Niepublikowana praca doktorska.Tyt. z ekranu tyt.Praca doktorska. University of Science and Technology AGH in Kraków. Faculty of Computer Science, Electronics and Telecommunications. Department of Computer Science, 2014.Zawiera bibliogr.Dostępna również w wersji drukowanej.Tryb dostępu: Internet.Grid computing, services and cloud infrastructures, evolution of Grid computing, virtual organizations, models of virtual organizations, contracts in virtual organizations, virtual organizations in grid computing, existing Grid environments, globus toolkit, UNICORE, gLite, QosCosGrid, most important standards and technologies in Grid computing, OGSA, WS-resource framework, security, information and monitoring services, interoperability between Grid frameworks, service oriented architectures, SOAP, WSDL, UDDI and WS-I, BPEL and WS-CDL, REST, enterprise service bus, P2P computing, emergence of cloud computing paradigm, metadata and ontologies, metadata in general, metadata in computing systems, Simple Knowledge Organization System SKOS, GLUE Schema, Common Information Model, knowledge representation formalisms, description logics, OWL Web Ontology Language, OWL 2, Semantic Web Knowledge Bases, unification of metadata in distributed computing infrastructures, through ontologies, motivation for metadata unification, description logics as metadata representation formalism, ontology separation scheme, Generic Grid Ontologies, ontology of resources, ontology of data, ontology of services, example use case, integration of common information model metadata scheme to OWL, managing semantic metadata with Grid Organizational Memory, requirements for a Grid semantic metadata repository, architecture of Grid Organizational Memory, GOM architecture, GOM engine, engine manager, deployer, GOMAdmin, proxy, protege plugin GOMTab, usage scenarios, performance evaluation, GOM Event System and knowledge evolution, GOM Peer-to-peer distribution model, interfacing Legacy Metadata Systems, LDAP integration to semantic knowledge base, semantic framework for virtual organizations, semantic approach to virtual organizations, framework architecture, support for contract negotiation, contract negotiation model, contract negotiation interfac