270 research outputs found

    Building a self-adaptive content distribution network

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    Challenges for Trusted Computing

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    This article identifies and discusses some of the key challenges that need to be addressed if the vision of Trusted Computing is to become reality. Topics addressed include issues with setting up and maintaining the PKI required to support the full set of Trusted Computing functionality, the practical use and verification of attestation evidence, and backwards compatibility, usability and compliance issues

    Autonomic Computing: the natural fusion of Soft Computing and Hard Computing

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    Abstract- Autonomic Computing is emerging as a significant new approach in the design of computing systems. Its overall goal is the creation of Self-Managing Systems. In order to achieve this, Hard and So3 Computing are required. The benefits from utilizing Soy Computing include their ability to handle imprecision, uncertainty and partial truth that is inherently present in any complex real world problem accompanied by the practicable benefits of Hard Computing namely the stability of highly predictable solutions and typically low computational burden. This paper motivates the proposition that the successful creation of Autonomic Systems requires a fusion of Soj? Computing and Hard Computing

    A Health-Check Model for Autonomic Systems Based on a Pulse Monitor

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    Modeling ontology views: An abstract view model for semantic web

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    The emergence of Semantic Web (SW) and the related technologies promise to make the web a meaningful experience. However, high level modelling, design and querying techniques proves to be a challenging task for organizations that are hoping to utilize the SW paradigm for their industrial applications. To address one such issue, in this paper, we propose an abstract view model with conceptual extensions for the SW. First we outline the view model, its properties and some modelling issues with the help of an industrial case study example. Then, we provide some discussions on constructing such views (at the conceptual level) using a set of operators. Later we provide a brief discussion on how such this view model can utilized in the MOVE [1] system, to design and construct materialized Ontology views to support Ontology extraction

    Conceptual design of an XML FACT repository for dispersed XML document warehouses and XML marts

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    Since the introduction of eXtensible Markup Language (XML), XML repositories have gained a foothold in many global (and government) organizations, where, e-Commerce and e-business models have maturated in handling daily transactional data among heterogeneous information systems in multi-data formats. Due to this, the amount of data available for enterprise decision-making process is increasing exponentially and are being stored and/or communicated in XML. This presents an interesting challenge to investigate models, frameworks and techniques for organizing and analyzing such voluminous, yet distributed XML documents for business intelligence in the form of XML warehouse repositories and XML marts. In this paper, we address such an issue, where we propose a view-driven approach for modelling and designing of a Global XML FACT (GxFACT) repository under the MDA initiatives. Here we propose the GxFACT using logically grouped, geographically dispersed, XML document warehouses and Document Marts in a global enterprise setting. To deal with organizations? evolving decision-making needs, we also provide three design strategies for building and managing of such GxFACT in the context of modelling of further hierarchical dimensions and/or global document warehouses

    Engineering XML solutions using views

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    In industrial informatics, engineering data intensive Enterprise Information Systems (EIS) is a challenging task without abstraction and partitioning. Further, the introduction of semi-structured data (namely XML) and its rapid adaptation by the commercial and industrial systems increased the complexity for data engineering. Conversely, the introduction of OMG's MDA presents an interesting paradigm for EIS and system modelling, where a system is designed at a higher level of abstraction. This presents an interesting problem to investigate data engineering XML solutions under the MDA initiatives, where, models and framework requires higher level of abstraction. In this paper we investigate a view model that can provide layered design methodology for modelling data intensive XML solutions for EIS paradigm, with sufficient level of abstraction

    Autonomic Analytics

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    A layered view model for XML with conceptual and logical extensions, and its applications

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    University of Technology, Sydney. Faculty of Information Technology.EXtensible Markup Language (XML) is becoming the dominant standard for storing, describing and interchanging data among various Enterprises Information Systems (EIS), web repositories and databases. With this increasing reliance on such self-describing, schema-based, semi-structured data language XML, there exists a need to model, design, and manipulate XML and associated semantics at a higher level of abstraction than at the instance level. However, existing OO conceptual modelling languages provide insufficient modelling constructs for utilizing XML structures, descriptions and constraints, and XML and associated schema languages lack the ability to provide higher levels of abstraction, such as conceptual models that are easily understood by humans. To this end, it is interesting to investigate conceptual and schema formalisms as a means of providing higher level semantics in the context of XML-related data modelling. In particular we note that there is a strong need to model views of XML repositories at the conceptual level. This is in contrast to the situation for views for the relational model which are generally defined at the implementation level. In this research, we use XML view and introduce the Layered View Model (LVM, for short), a declarative conceptual framework for specifying and defining views at a higher level of abstraction. The views in the LVM are specified using explicit conceptual, logical and instance level semantics and provide declarative transformation between these levels of abstraction. For such a task, an elaborated and enhanced OO based modelling and transformation methodology is employed. The LVM framework leads to a number of interesting problems that are studied in this research. First we address the issue of conceptualizing the notion of views: the clear separation of conceptual concerns from the implementation and data language concerns. Here, the LVM views are considered as first-class citizens of the conceptual model. Second we provide formal semantics and definitions to enforce representation, specification and definition of such views at the highest level of abstraction, the conceptual level. Third we address the issue of modelling and transformation of LVM views to the required level of abstraction, namely to the schema and instance levels. Finally, we apply LVM to real-world data modelling scenarios to develop other architectural frameworks in the domains such as dimensional XML data modelling, ontology views in the Semantic Web paradigm and modelling user-centred websites and web portals
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