14,456 research outputs found

    Domino: exploring mobile collaborative software adaptation

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    Social Proximity Applications (SPAs) are a promising new area for ubicomp software that exploits the everyday changes in the proximity of mobile users. While a number of applications facilitate simple file sharing between coā€“present users, this paper explores opportunities for recommending and sharing software between users. We describe an architecture that allows the recommendation of new system components from systems with similar histories of use. Software components and usage histories are exchanged between mobile users who are in proximity with each other. We apply this architecture in a mobile strategy game in which players adapt and upgrade their game using components from other players, progressing through the game through sharing tools and history. More broadly, we discuss the general application of this technique as well as the security and privacy challenges to such an approach

    MOSAIC roadmap for mobile collaborative work related to health and wellbeing.

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    The objective of the MOSAIC project is to accelerate innovation in Mobile Worker Support Environments. For that purpose MOSAIC develops visions and illustrative scenarios for future collaborative workspaces involving mobile and location-aware working. Analysis of the scenarios is input to the process of road mapping with the purpose of developing strategies for R&D leading to deployment of innovative mobile work technologies and applications across different domains. One of the application domains where MOSAIC is active is health and wellbeing. This paper builds on another paper submitted to this same conference, which presents and discusses health care and wellbeing specific scenarios. The aim is to present an early form of a roadmap for validation

    Transparent multi-core speculative parallelization of DES models with event and cross-state dependencies

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    In this article we tackle transparent parallelization of Discrete Event Simulation (DES) models to be run on top of multi-core machines according to speculative schemes. The innovation in our proposal lies in that we consider a more general programming and execution model, compared to the one targeted by state of the art PDES platforms, where the boundaries of the state portion accessible while processing an event at a specific simulation object do not limit access to the actual object state, or to shared global variables. Rather, the simulation object is allowed to access (and alter) the state of any other object, thus causing what we term cross-state dependency. We note that this model exactly complies with typical (easy to manage) sequential-style DES programming, where a (dynamically-allocated) state portion of object A can be accessed by object B in either read or write mode (or both) by, e.g., passing a pointer to B as the payload of a scheduled simulation event. However, while read/write memory accesses performed in the sequential run are always guaranteed to observe (and to give rise to) a consistent snapshot of the state of the simulation model, consistency is not automatically guaranteed in case of parallelization and concurrent execution of simulation objects with cross-state dependencies. We cope with such a consistency issue, and its application-transparent support, in the context of parallel and optimistic executions. This is achieved by introducing an advanced memory management architecture, able to efficiently detect read/write accesses by concurrent objects to whichever object state in an application transparent manner, together with advanced synchronization mechanisms providing the advantage of exploiting parallelism in the underlying multi-core architecture while transparently handling both cross-state and traditional event-based dependencies. Our proposal targets Linux and has been integrated with the ROOT-Sim open source optimistic simulation platform, although its design principles, and most parts of the developed software, are of general relevance. Copyright 2014 ACM

    A canonical theory of dynamic decision-making

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    Decision-making behavior is studied in many very different fields, from medicine and eco- nomics to psychology and neuroscience, with major contributions from mathematics and statistics, computer science, AI, and other technical disciplines. However the conceptual- ization of what decision-making is and methods for studying it vary greatly and this has resulted in fragmentation of the field. A theory that can accommodate various perspectives may facilitate interdisciplinary working. We present such a theory in which decision-making is articulated as a set of canonical functions that are sufficiently general to accommodate diverse viewpoints, yet sufficiently precise that they can be instantiated in different ways for specific theoretical or practical purposes. The canons cover the whole decision cycle, from the framing of a decision based on the goals, beliefs, and background knowledge of the decision-maker to the formulation of decision options, establishing preferences over them, and making commitments. Commitments can lead to the initiation of new decisions and any step in the cycle can incorporate reasoning about previous decisions and the rationales for them, and lead to revising or abandoning existing commitments. The theory situates decision-making with respect to other high-level cognitive capabilities like problem solving, planning, and collaborative decision-making. The canonical approach is assessed in three domains: cognitive and neuropsychology, artificial intelligence, and decision engineering

    Policy Conflict Analysis in Distributed System Management

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    Contextual mobile adaptation

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    Ubiquitous computing (ubicomp) involves systems that attempt to fit in with usersā€™ context and interaction. Researchers agree that system adaptation is a key issue in ubicomp because it can be hard to predict changes in contexts, needs and uses. Even with the best planning, it is impossible to foresee all uses of software at the design stage. In order for software to continue to be helpful and appropriate it should, ideally, be as dynamic as the environment in which it operates. Changes in user requirements, contexts of use and system resources mean software should also adapt to better support these changes. An area in which adaptation is clearly lacking is in ubicomp systems, especially those designed for mobile devices. By improving techniques and infrastructure to support adaptation it is possible for ubicomp systems to not only sense and adapt to the environments they are running in, but also retrieve and install new functionality so as to better support the dynamic context and needs of users in such environments. Dynamic adaptation of software refers to the act of changing the structure of some part of a software system as it executes, without stopping or restarting it. One of the core goals of this thesis is to discover if such adaptation is feasible, useful and appropriate in the mobile environment, and how designers can create more adaptive and flexible ubicomp systems and associated user experiences. Through a detailed study of existing literature and experience of several early systems, this thesis presents design issues and requirements for adaptive ubicomp systems. This thesis presents the Domino framework, and demonstrates that a mobile collaborative software adaptation framework is achievable. This system can recommend future adaptations based on a history of use. The framework demonstrates that wireless network connections between mobile devices can be used to transport usage logs and software components, with such connections made either in chance encounters or in designed multiā€“user interactions. Another aim of the thesis is to discover if users can comprehend and smoothly interact with systems that are adapting. To evaluate Domino, a multiplayer game called Castles has been developed, in which game buildings are in fact software modules that are recommended and transferred between players. This evaluation showed that people are comfortable receiving semiā€“automated software recommendations; these complement traditional recommendation methods such as word of mouth and online forums, with the systemā€™s support freeing users to discuss more inā€“depth aspects of the system, such as tactics and strategies for use, rather than forcing them to discover, acquire and integrate software by themselves
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