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  • 1.
    Elsts, Atis
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Optimal Task Allocation in Sensor and Actuator Networks2015In: Proc. 11th Swedish National Computer Networking Workshop, 2015Conference paper (Refereed)
    Abstract [en]

    Sensor and actuator network macroprogramming techniques that use task graphs are promising options for high-level application development in this domain. However, setting up a multitude of application-level tasks in the network and subsequently keeping track of them is a nontrivial undertaking. Therefore, tool support for automated task allocation is required. Such a support is typically implemented by providing an objective function that evaluates the cost of a task mapping, and a search algorithm that attempts to minimize this function.The current algorithms for task allocation in sensor and actuator networks either do not guarantee optimal results, or are conceptually tied to a single specific objective function. Our work contributes to this state-of-art in two aspects: firstly, by finding a model that can easily accommodate several different objective functions, and secondly, by finding a search strategy that makes it feasible to allocate realistic task graphs even in large networks.

  • 2.
    Elsts, Atis
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Hassani Bijarbooneh, Farshid
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Jacobsson, Martin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Architecture and Computer Communication.
    Sagonas, Konstantinos
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Enabling design of performance-controlled sensor network applications through task allocation and reallocation2015In: Proc. 11th International Conference on Distributed Computing in Sensor Systems, IEEE Computer Society, 2015, p. 248-253Conference paper (Refereed)
    Abstract [en]

    Task Graph (ATaG) is a sensor network application development paradigm where the application is visually described by a graph where the nodes correspond to application-level tasks and edges correspond to dataflows. We extend ATaG with the option to add nonfunctional requirements: constraints on end-to-end delay and packet delivery rate. Setting up these constraints at the design phase naturally leads to enabling run-time assurance at the deployment phase, when the conditions of the constraints are used as network's performance goals. We provide both run-time middleware that checks the conditions of these constraints and a central management unit that dynamically adapts the system by doing task reallocation and putting task copies on redundant nodes. Through extensive simulations we show that the system is efficient enough to enable adaptations within tens of seconds even in large networks.

  • 3.
    Elsts, Atis
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Hassani Bijarbooneh, Farshid
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Jacobsson, Martin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Architecture and Computer Communication.
    Sagonas, Konstantinos
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    ProFuN TG: A tool for programming and managing performance-aware sensor network applications2015In: IEEE 40th Local Computer Networks Conference Workshops (LCN Workshops), IEEE Computer Society, 2015, p. 751-759Conference paper (Refereed)
    Abstract [en]

    Sensor network macroprogramming methodologiessuch as the Abstract Task Graph hold the promise of enablinghigh-level sensor network application development. However,progress in this area is hampered by the scarcity of tools, andalso because of insufficient focus on developing tool support forprogramming applications aware of performance requirements.

    We present ProFuN TG (Task Graph), a tool for designing sen-sor network applications using task graphs. ProFuN TG providesautomated task mapping, sensor node firmware macrocompila-tion, application simulation, deployment, and runtime mainte-nance capabilities. It allows users to incorporate performancerequirements in the applications, expressed through constraintson task-to-task dataflows. The tool includes middleware that usesan efficient flooding-based protocol to set up tasks in the network,and also enables runtime assurance by keeping track of theconstraint conditions.

    We show that the adaptive task reallocation enabled by ourapproach can significantly increase application reliability whiledecreasing energy consumption: in a network with unreliablelinks, we achieve above 99.89 % task-to-task PDR while keepingthe maximal radio duty cycle around 2.0 %.

  • 4.
    Elsts, Atis
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Hassani Bijarbooneh, Farshid
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Jacobsson, Martin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Architecture and Computer Communication.
    Sagonas, Konstantinos
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    ProFuN TG: A Tool Using Abstract Task Graphs to Facilitate the Development, Deployment and Maintenance of Wireless Sensor Network Applications2015In: Proc. Poster/Demo Session: 12th European Conference on Wireless Sensor Networks, 2015, p. 19-20Conference paper (Refereed)
    Abstract [en]

    In this demo abstract we present ProFuN TG (Task Graph), a tool for sensor network application development using the data-flow programming paradigm. The tool has support for the whole lifecycle of WSN application: from the initial design of its task graph, task placement on network nodes, execution in a simulated environment, deployment on real hardware, to its automated maintenance through task remapping. ProFuN TG allows to program applications that incorporate quality-of-service requirements, expressed through constraints on task-to-task data flows.

  • 5.
    Elsts, Atis
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Hassani Bijarbooneh, Farshid
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Jacobsson, Martin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Architecture and Computer Communication.
    Sagonas, Konstantinos
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    ProFuN TG: Programming Sensornets with Task Graphs for Increased Reliability and Energy-Efficiency2015Conference paper (Refereed)
    Abstract [en]

    Sensor network macroprogramming methodologies such as the Abstract Task Graph hold the promise of enabling high-level sensor network application development. However, progress in this area is hampered by the scarcity of tools, and also because of insufficient focus on developing tool support for programming applications aware of performance requirements.

    In this demo we present ProFuN TG (Task Graph), a tool for designing sensor network applications using task graphs. ProFuN TG provides automated task mapping, sensor nodefirmware macrocompilation, application simulation, deployment, and runtime maintenance capabilities. It allows users to incorporate performance requirements in the applications, expressed through constraints on task-to-task dataflows. The tool includes middleware that uses an efficient flooding-based protocol to set up tasks in the network, and also enables runtime assurance by keeping track of the constraint conditions.

    Through task allocation in a way that optimizes an objective function in a model of the network, and adaptive task reallocation in case of link, node, or sensor failures the tool helps to make sensornet applications both more energy-efficient and reliable.

  • 6.
    Elsts, Atis
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science.
    Ngai, Edith C.-H.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    A Case for Node-Local Runtime Parameter Adaptation in Wireless Sensor Networks2014In: Proc. 10th Swedish National Computer Networking Workshop, 2014Conference paper (Other academic)
    Abstract [en]

    The challenges posed to wireless sensor networks by the environments they are deployed cannot always be predicted beforehand. Therefore, adaptive behavior at the run-time may be required to achieve good reliability and energy-efficiency. We present a node-local runtime adaptation algorithm that adapts the over-the-air message encoding based on presence of weak links and external interference in the immediate neighborhood of the node. Evaluation with a network simulator shows that this algorithm leads to significant network-wide reduction of radio duty cycle under specific radio transmission failure models.

1 - 6 of 6
CiteExportLink to result list
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  • de-DE
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  • nn-NO
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