960 resultados para User-centric API Framework


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In the past few years the so-called gadgets like cellular phones, personal data assistants and digital cameras are more widespread even with less technological aware users. However, for several reasons, the factory-floor itself seems to be hermetic to this changes ... After the fieldbus revolution, the factory-floor has seen an increased use of more and more powerful programmable logic controllers and user interfaces but the way they are used remains almost the same. We believe that new user-computer interaction techniques including multimedia and augmented rcaliry combined with now affordable technologies like wearable computers and wireless networks can change the way the factory personal works together with the roachines and the information system on the factory-floor. This new age is already starting with innovative uses of communication networks on the factory-floor either using "standard" networks or enhancing industrial networks with multimedia and wireless capabilities.

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Virtual and augmented reality (VR/AR) are increasingly being used in various business scenarios and are important driving forces in technology development. However the usage of these technologies in the home environment is restricted due to several factors including lack of low-cost (from the client point of view) highperformance solutions. In this paper we present a general client/server rendering architecture based on Real-Time concepts, including support for a wide range of client platforms and applications. The idea of focusing on the real-time behaviour of all components involved in distributed IP-based VR scenarios is new and has not been addressed before, except for simple sub-solutions. This is considered as “the most significant problem with the IP environment” [1]. Thus, the most important contribution of this research will be the holistic approach, in which networking, end-systems and rendering aspects are integrated into a cost-effective infrastructure for building distributed real-time VR applications on IP-based networks.

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It is generally challenging to determine end-to-end delays of applications for maximizing the aggregate system utility subject to timing constraints. Many practical approaches suggest the use of intermediate deadline of tasks in order to control and upper-bound their end-to-end delays. This paper proposes a unified framework for different time-sensitive, global optimization problems, and solves them in a distributed manner using Lagrangian duality. The framework uses global viewpoints to assign intermediate deadlines, taking resource contention among tasks into consideration. For soft real-time tasks, the proposed framework effectively addresses the deadline assignment problem while maximizing the aggregate quality of service. For hard real-time tasks, we show that existing heuristic solutions to the deadline assignment problem can be incorporated into the proposed framework, enriching their mathematical interpretation.

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Tese de doutoramento em Ciências da Educação, área de Teoria Curricular e Ensino das Ciências

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Embedded real-time applications increasingly present high computation requirements, which need to be completed within specific deadlines, but that present highly variable patterns, depending on the set of data available in a determined instant. The current trend to provide parallel processing in the embedded domain allows providing higher processing power; however, it does not address the variability in the processing pattern. Dimensioning each device for its worst-case scenario implies lower average utilization, and increased available, but unusable, processing in the overall system. A solution for this problem is to extend the parallel execution of the applications, allowing networked nodes to distribute the workload, on peak situations, to neighbour nodes. In this context, this report proposes a framework to develop parallel and distributed real-time embedded applications, transparently using OpenMP and Message Passing Interface (MPI), within a programming model based on OpenMP. The technical report also devises an integrated timing model, which enables the structured reasoning on the timing behaviour of these hybrid architectures.

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Stringent cost and energy constraints impose the use of low-cost and low-power radio transceivers in large-scale wireless sensor networks (WSNs). This fact, together with the harsh characteristics of the physical environment, requires a rigorous WSN design. Mechanisms for WSN deployment and topology control, MAC and routing, resource and mobility management, greatly depend on reliable link quality estimators (LQEs). This paper describes the RadiaLE framework, which enables the experimental assessment, design and optimization of LQEs. RadiaLE comprises (i) the hardware components of the WSN testbed and (ii) a software tool for setting-up and controlling the experiments, automating link measurements gathering through packets-statistics collection, and analyzing the collected data, allowing for LQEs evaluation. We also propose a methodology that allows (i) to properly set different types of links and different types of traffic, (ii) to collect rich link measurements, and (iii) to validate LQEs using a holistic and unified approach. To demonstrate the validity and usefulness of RadiaLE, we present two case studies: the characterization of low-power links and a comparison between six representative LQEs. We also extend the second study for evaluating the accuracy of the TOSSIM 2 channel model.

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This work focuses on highly dynamic distributed systems with Quality of Service (QoS) constraints (most importantly real-time constraints). To that purpose, real-time applications may benefit from code offloading techniques, so that parts of the application can be offloaded and executed, as services, by neighbour nodes, which are willing to cooperate in such computations. These applications explicitly state their QoS requirements, which are translated into resource requirements, in order to evaluate the feasibility of accepting other applications in the system.

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Several projects in the recent past have aimed at promoting Wireless Sensor Networks as an infrastructure technology, where several independent users can submit applications that execute concurrently across the network. Concurrent multiple applications cause significant energy-usage overhead on sensor nodes, that cannot be eliminated by traditional schemes optimized for single-application scenarios. In this paper, we outline two main optimization techniques for reducing power consumption across applications. First, we describe a compiler based approach that identifies redundant sensing requests across applications and eliminates those. Second, we cluster the radio transmissions together by concatenating packets from independent applications based on Rate-Harmonized Scheduling.

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Wireless Sensor Networks (WSNs) are increasingly used in various application domains like home-automation, agriculture, industries and infrastructure monitoring. As applications tend to leverage larger geographical deployments of sensor networks, the availability of an intuitive and user friendly programming abstraction becomes a crucial factor in enabling faster and more efficient development, and reprogramming of applications. We propose a programming pattern named sMapReduce, inspired by the Google MapReduce framework, for mapping application behaviors on to a sensor network and enabling complex data aggregation. The proposed pattern requires a user to create a network-level application in two functions: sMap and Reduce, in order to abstract away from the low-level details without sacrificing the control to develop complex logic. Such a two-fold division of programming logic is a natural-fit to typical sensor networking operation which makes sensing and topological modalities accessible to the user.

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As the complexity of embedded systems increases, multiple services have to compete for the limited resources of a single device. This situation is particularly critical for small embedded devices used in consumer electronics, telecommunication, industrial automation, or automotive systems. In fact, in order to satisfy a set of constraints related to weight, space, and energy consumption, these systems are typically built using microprocessors with lower processing power and limited resources. The CooperatES framework has recently been proposed to tackle these challenges, allowing resource constrained devices to collectively execute services with their neighbours in order to fulfil the complex Quality of Service (QoS) constraints imposed by users and applications. In order to demonstrate the framework's concepts, a prototype is being implemented in the Android platform. This paper discusses key challenges that must be addressed and possible directions to incorporate the desired real-time behaviour in Android.

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ARINC specification 653-2 describes the interface between application software and underlying middleware in a distributed real-time avionics system. The real-time workload in this system comprises of partitions, where each partition consists of one or more processes. Processes incur blocking and preemption overheads and can communicate with other processes in the system. In this work we develop compositional techniques for automated scheduling of such partitions and processes. At present, system designers manually schedule partitions based on interactions they have with the partition vendors. This approach is not only time consuming, but can also result in under utilization of resources. In contrast, the technique proposed in this paper is a principled approach for scheduling ARINC-653 partitions and therefore should facilitate system integration.

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In distributed soft real-time systems, maximizing the aggregate quality-of-service (QoS) is a typical system-wide goal, and addressing the problem through distributed optimization is challenging. Subtasks are subject to unpredictable failures in many practical environments, and this makes the problem much harder. In this paper, we present a robust optimization framework for maximizing the aggregate QoS in the presence of random failures. We introduce the notion of K-failure to bound the effect of random failures on schedulability. Using this notion we define the concept of K-robustness that quantifies the degree of robustness on QoS guarantee in a probabilistic sense. The parameter K helps to tradeoff achievable QoS versus robustness. The proposed robust framework produces optimal solutions through distributed computations on the basis of Lagrangian duality, and we present some implementation techniques. Our simulation results show that the proposed framework can probabilistically guarantee sub-optimal QoS which remains feasible even in the presence of random failures.

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In this paper we propose a framework for the support of mobile application with Quality of Service (QoS) requirements, such as voice or video, capable of supporting distributed, migration-capable, QoS-enabled applications on top of the Android Operating system.

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Link quality estimation is a fundamental building block for the design of several different mechanisms and protocols in wireless sensor networks (WSN). A thorough experimental evaluation of link quality estimators (LQEs) is thus mandatory. Several WSN experimental testbeds have been designed ([1–4]) but only [3] and [2] targeted link quality measurements. However, these were exploited for analyzing low-power links characteristics rather than the performance of LQEs. Despite its importance, the experimental performance evaluation of LQEs remains an open problem, mainly due to the difficulty to provide a quantitative evaluation of their accuracy. This motivated us to build a benchmarking testbed for LQE - RadiaLE, which we present here as a demo. It includes (i.) hardware components that represent the WSN under test and (ii.) a software tool for the set up and control of the experiments and also for analyzing the collected data, allowing for LQEs evaluation.

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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do grau de Mestre em Engenharia Informática.