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ProFuN TG: Programming Sensornets with Task Graphs for Increased Reliability and Energy-Efficiency
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science. (Programming Languages)
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science. (ASTRA)
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Architecture and Computer Communication. (Communication Research)ORCID iD: 0000-0002-8359-5745
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science. (Programming Languages)
2015 (English)Conference paper, Poster (with or without abstract) (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.

Place, publisher, year, edition, pages
IEEE Computer Society, 2015.
National Category
Communication Systems Embedded Systems
Research subject
Computer Science with specialization in Computer Communication
Identifiers
URN: urn:nbn:se:uu:diva-288533OAI: oai:DiVA.org:uu-288533DiVA: diva2:924240
Conference
The 40th IEEE Conference on Local Computer Networks (LCN)
Projects
ProFuN
Funder
Swedish Foundation for Strategic Research , RIT08-0065
Available from: 2016-04-28 Created: 2016-04-28 Last updated: 2016-07-01Bibliographically approved

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fulltext(1336 kB)62 downloads
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http://www.ieeelcn.org/prior/LCN40/lcn40demos/Elsts.pdf

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Elsts, AtisHassani Bijarbooneh, FarshidJacobsson, MartinSagonas, Konstantinos

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CiteExportLink to record
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Citation style
  • apa
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Output format
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