9,173 research outputs found

    Supporting Management lnteraction and Composition of Self-Managed Cells

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    Management in ubiquitous systems cannot rely on human intervention or centralised decision-making functions because systems are complex and devices are inherently mobile and cannot refer to centralised management applications for reconfiguration and adaptation directives. Management must be devolved, based on local decision-making and feedback control-loops embedded in autonomous components. Previous work has introduced a Self-Managed Cell (SMC) as an infrastructure for building ubiquitous applications. An SMC consists of a set of hardware and software components that implement a policy-driven feedback control-loop. This allows SMCs to adapt continually to changes in their environment or in their usage requirements. Typical applications include body-area networks for healthcare monitoring, and communities of unmanned autonomous vehicles (UAVs) for surveillance and reconnaissance operations. Ubiquitous applications are typically formed from multiple interacting autonomous components, which establish peer-to-peer collaborations, federate and compose into larger structures. Components must interact to distribute management tasks and to enforce communication strategies. This thesis presents an integrated framework which supports the design and the rapid establishment of policy-based SMC interactions by systematically composing simpler abstractions as building elements of a more complex collaboration. Policy-based interactions are realised – subject to an extensible set of security functions – through the exchanges of interfaces, policies and events, and our framework was designed to support the specification, instantiation and reuse of patterns of interaction that prescribe the manner in which these exchanges are achieved. We have defined a library of patterns that provide reusable abstractions for the structure, task-allocation and communication aspects of an interaction, which can be individually combined for building larger policy-based systems in a methodical manner. We have specified a formal model to ensure the rigorous verification of SMC interactions before policies are deployed in physical devices. A prototype has been implemented that demonstrates the practical feasibility of our framework in constrained resources

    Modelling and analyzing adaptive self-assembling strategies with Maude

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    Building adaptive systems with predictable emergent behavior is a challenging task and it is becoming a critical need. The research community has accepted the challenge by introducing approaches of various nature: from software architectures, to programming paradigms, to analysis techniques. We recently proposed a conceptual framework for adaptation centered around the role of control data. In this paper we show that it can be naturally realized in a reflective logical language like Maude by using the Reflective Russian Dolls model. Moreover, we exploit this model to specify, validate and analyse a prominent example of adaptive system: robot swarms equipped with self-assembly strategies. The analysis exploits the statistical model checker PVeStA

    Proceedings of the 3rd Workshop on Domain-Specific Language Design and Implementation (DSLDI 2015)

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    The goal of the DSLDI workshop is to bring together researchers and practitioners interested in sharing ideas on how DSLs should be designed, implemented, supported by tools, and applied in realistic application contexts. We are both interested in discovering how already known domains such as graph processing or machine learning can be best supported by DSLs, but also in exploring new domains that could be targeted by DSLs. More generally, we are interested in building a community that can drive forward the development of modern DSLs. These informal post-proceedings contain the submitted talk abstracts to the 3rd DSLDI workshop (DSLDI'15), and a summary of the panel discussion on Language Composition

    Towards supporting interactions between self-managed cells

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    Architectures for smart end-user services in the power grid

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    Abstract-The increase of distributed renewable electricity generators, such as solar cells and wind turbines, requires a new energy management system. These distributed generators introduce bidirectional energy flows in the low-voltage power grid, requiring novel coordination mechanisms to balance local supply and demand. Closed solutions exist for energy management on the level of individual homes. However, no service architectures have been defined that allow the growing number of end-users to interact with the other power consumers and generators and to get involved in more rational energy consumption patterns using intuitive applications. We therefore present a common service architecture that allows houses with renewable energy generation and smart energy devices to plug into a distributed energy management system, integrated with the public power grid. Next to the technical details, we focus on the usability aspects of the end-user applications in order to contribute to high service adoption and optimal user involvement. The presented architecture facilitates end-users to reduce net energy consumption, enables power grid providers to better balance supply and demand, and allows new actors to join with new services. We present a novel simulator that allows to evaluate both the power grid and data communication aspects, and illustrate a 22% reduction of the peak load by deploying a central coordinator inside the home gateway of an end-user

    Going beyond Computation and Its Limits: Injecting Cognition into Computing

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    Overcoming the Newtonian Paradigm: The Unfinished Project of Theoretical Biology from a Schellingian Perspective

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    Defending Robert Rosen’s claim that in every confrontation between physics and biology it is physics that has always had to give ground, it is shown that many of the most important advances in mathematics and physics over the last two centuries have followed from Schelling’s demand for a new physics that could make the emergence of life intelligible. Consequently, while reductionism prevails in biology, many biophysicists are resolutely anti-reductionist. This history is used to identify and defend a fragmented but progressive tradition of anti-reductionist biomathematics. It is shown that the mathematicoephysico echemical morphology research program, the biosemiotics movement, and the relational biology of Rosen, although they have developed independently of each other, are built on and advance this antireductionist tradition of thought. It is suggested that understanding this history and its relationship to the broader history of post-Newtonian science could provide guidance for and justify both the integration of these strands and radically new work in post-reductionist biomathematics
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