488,238 research outputs found

    Federated and autonomic management of multimedia services

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    Over the years, the Internet has significantly evolved in size and complexity. Additionally, the modern multimedia services it offers have considerably more stringent Quality of Service (QoS) requirements than traditional static services. These factors contribute to the ever-increasing complexity and cost to manage the Internet and its services. In the dissertation, a novel network management architecture is proposed to overcome these problems. It supports QoS-guarantees of multimedia services across the Internet, by setting up end-to-end network federations. A network federation is defined as a persistent cross-organizational agreement that enables the cooperating networks to share capabilities. Additionally, the architecture incorporates aspects from autonomic network management to tackle the ever-growing management complexity of modern communications networks. Specifically, a hierarchical approach is presented, which guarantees scalable collaboration of huge amounts of self-governing autonomic management components

    Scaling Participation -- What Does the Concept of Managed Communities Offer for Participatory Design?

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    This paper investigates mechanisms for scaling participation in participatory design (PD). Specifically, the paper focuses on managed communities, one strategy of generification work. We first give a brief introduction on the issue of scaling in PD, followed by exploring the strategy of managed communities in PD. This exploration is underlined by an ongoing case study in the healthcare sector, and we propose solutions to observed challenges. The paper ends with a critical reflection on the possibilities managed communities offer for PD. Managed communities have much to offer beyond mere generification work for large-scale information systems, but we need to pay attention to core PD values that are in danger of being sidelined in the process

    Coordinating Knowledge Work in Multi-Team Programs: Findings from a Large-Scale Agile Development Program

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    Software development projects have undergone remarkable changes with the arrival of agile development methods. While intended for small, self-managing teams, these methods are increasingly used also for large development programs. A major challenge in programs is to coordinate the work of many teams, due to high uncertainty in tasks, a high degree of interdependence between tasks and because of the large number of people involved. This revelatory case study focuses on how knowledge work is coordinated in large-scale agile development programs by providing a rich description of the coordination practices used and how these practices change over time in a four year development program with 12 development teams. The main findings highlight the role of coordination modes based on feedback, the use of a number of mechanisms far beyond what is described in practitioner advice, and finally how coordination practices change over time. The findings are important to improve the outcome of large knowledge-based development programs by tailoring coordination practices to needs and ensuring adjustment over time.Comment: To appear in Project Management Journa

    Autonomic Cloud Computing: Open Challenges and Architectural Elements

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    As Clouds are complex, large-scale, and heterogeneous distributed systems, management of their resources is a challenging task. They need automated and integrated intelligent strategies for provisioning of resources to offer services that are secure, reliable, and cost-efficient. Hence, effective management of services becomes fundamental in software platforms that constitute the fabric of computing Clouds. In this direction, this paper identifies open issues in autonomic resource provisioning and presents innovative management techniques for supporting SaaS applications hosted on Clouds. We present a conceptual architecture and early results evidencing the benefits of autonomic management of Clouds.Comment: 8 pages, 6 figures, conference keynote pape

    A network approach for managing and processing big cancer data in clouds

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    Translational cancer research requires integrative analysis of multiple levels of big cancer data to identify and treat cancer. In order to address the issues that data is decentralised, growing and continually being updated, and the content living or archiving on different information sources partially overlaps creating redundancies as well as contradictions and inconsistencies, we develop a data network model and technology for constructing and managing big cancer data. To support our data network approach for data process and analysis, we employ a semantic content network approach and adopt the CELAR cloud platform. The prototype implementation shows that the CELAR cloud can satisfy the on-demanding needs of various data resources for management and process of big cancer data

    Constants in Future Cities and Regions

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    The paper resumes some of the conversations the authors had in three years of research, based on the review of best participatory planning practices worldwide. The case projects are selected and discussed with the protagonists across four leading issues: Simulation, Scenario and Visioning, Government and Governance, and Scale. The case-oriented discussion is a peculiarity of the book , contributing to give shape to future cities or regions. The aim is to build a critical thinking on how urban planning, policy and design issues are faced differently or similarly throughout every cases studied. The book include the description of computer models and media, socio-political experiments and professional practices which help communicating the future effects of different design, policy and planning strategies and schemes with a wide range of aims: from information, through consultation, towards active participation. The cases have confirmed that simulation tools can impact on local government and can drive new forms of "glocal" governance, shaping and implementing future plans and projects at different scale and time span. The following paragraphs will point at some of the constant thoughts the authors had around the selection and editing of the book's case studied and related issue

    Models of everywhere revisited: a technological perspective

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    The concept ‘models of everywhere’ was first introduced in the mid 2000s as a means of reasoning about the environmental science of a place, changing the nature of the underlying modelling process, from one in which general model structures are used to one in which modelling becomes a learning process about specific places, in particular capturing the idiosyncrasies of that place. At one level, this is a straightforward concept, but at another it is a rich multi-dimensional conceptual framework involving the following key dimensions: models of everywhere, models of everything and models at all times, being constantly re-evaluated against the most current evidence. This is a compelling approach with the potential to deal with epistemic uncertainties and nonlinearities. However, the approach has, as yet, not been fully utilised or explored. This paper examines the concept of models of everywhere in the light of recent advances in technology. The paper argues that, when first proposed, technology was a limiting factor but now, with advances in areas such as Internet of Things, cloud computing and data analytics, many of the barriers have been alleviated. Consequently, it is timely to look again at the concept of models of everywhere in practical conditions as part of a trans-disciplinary effort to tackle the remaining research questions. The paper concludes by identifying the key elements of a research agenda that should underpin such experimentation and deployment
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