5,922 research outputs found

    Overlay networks for smart grids

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    Self-managed cells and their federation

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    Future e-Health systems will consist of low-power, on-body wireless sensors attached to mobile users that interact with a ubiquitous computing environment. This kind of system needs to be able to configure itself with little or no user input; more importantly, it is required to adapt autonomously to changes such as user movement, device failure, the addition or loss of services, and proximity to other such systems. This extended abstract describes the basic architecture of a Self-Managed Cell (SMC) to address these requirements, and discusses various forms of federation between/among SMCs. This structure is motivated by a typical e-Health scenario

    Managed ecosystems of networked objects

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    Small embedded devices such as sensors and actuators will become the cornerstone of the Future Internet. To this end, generic, open and secure communication and service platforms are needed in order to be able to exploit the new business opportunities these devices bring. In this paper, we evaluate the current efforts to integrate sensors and actuators into the Internet and identify the limitations at the level of cooperation of these Internet-connected objects and the possible intelligence at the end points. As a solution, we propose the concept of Managed Ecosystem of Networked Objects, which aims to create a smart network architecture for groups of Internet-connected objects by combining network virtualization and clean-slate end-to-end protocol design. The concept maps to many real-life scenarios and should empower application developers to use sensor data in an easy and natural way. At the same time, the concept introduces many new challenging research problems, but their realization could offer a meaningful contribution to the realization of the Internet of Things

    Mobile Computing in Digital Ecosystems: Design Issues and Challenges

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    In this paper we argue that the set of wireless, mobile devices (e.g., portable telephones, tablet PCs, GPS navigators, media players) commonly used by human users enables the construction of what we term a digital ecosystem, i.e., an ecosystem constructed out of so-called digital organisms (see below), that can foster the development of novel distributed services. In this context, a human user equipped with his/her own mobile devices, can be though of as a digital organism (DO), a subsystem characterized by a set of peculiar features and resources it can offer to the rest of the ecosystem for use from its peer DOs. The internal organization of the DO must address issues of management of its own resources, including power consumption. Inside the DO and among DOs, peer-to-peer interaction mechanisms can be conveniently deployed to favor resource sharing and data dissemination. Throughout this paper, we show that most of the solutions and technologies needed to construct a digital ecosystem are already available. What is still missing is a framework (i.e., mechanisms, protocols, services) that can support effectively the integration and cooperation of these technologies. In addition, in the following we show that that framework can be implemented as a middleware subsystem that enables novel and ubiquitous forms of computation and communication. Finally, in order to illustrate the effectiveness of our approach, we introduce some experimental results we have obtained from preliminary implementations of (parts of) that subsystem.Comment: Proceedings of the 7th International wireless Communications and Mobile Computing conference (IWCMC-2011), Emergency Management: Communication and Computing Platforms Worksho

    Reconfigurable service-oriented architecture for autonomic computing

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    Almost a decade has passed since the objectives and benefits of autonomic computing were stated, yet even the latest system designs and deployments exhibit only limited and isolated elements of autonomic functionality. In previous work, we identified several of the key challenges behind this delay in the adoption of autonomic solutions, and proposed a generic framework for the development of autonomic computing systems that overcomes these challenges. In this article, we describe how existing technologies and standards can be used to realise our autonomic computing framework, and present its implementation as a service-oriented architecture. We show how this implementation employs a combination of automated code generation, model-based and object-oriented development techniques to ensure that the framework can be used to add autonomic capabilities to systems whose characteristics are unknown until runtime. We then use our framework to develop two autonomic solutions for the allocation of server capacity to services of different priorities and variable workloads, thus illustrating its application in the context of a typical data-centre resource management problem

    Robotic ubiquitous cognitive ecology for smart homes

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    Robotic ecologies are networks of heterogeneous robotic devices pervasively embedded in everyday environments, where they cooperate to perform complex tasks. While their potential makes them increasingly popular, one fundamental problem is how to make them both autonomous and adaptive, so as to reduce the amount of preparation, pre-programming and human supervision that they require in real world applications. The project RUBICON develops learning solutions which yield cheaper, adaptive and efficient coordination of robotic ecologies. The approach we pursue builds upon a unique combination of methods from cognitive robotics, machine learning, planning and agent- based control, and wireless sensor networks. This paper illustrates the innovations advanced by RUBICON in each of these fronts before describing how the resulting techniques have been integrated and applied to a smart home scenario. The resulting system is able to provide useful services and pro-actively assist the users in their activities. RUBICON learns through an incremental and progressive approach driven by the feed- back received from its own activities and from the user, while also self-organizing the manner in which it uses available sensors, actuators and other functional components in the process. This paper summarises some of the lessons learned by adopting such an approach and outlines promising directions for future work
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