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ProFuN TG: A tool for programming and managing performance-aware sensor network applications
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)In: IEEE 40th Local Computer Networks Conference Workshops (LCN Workshops), IEEE Computer Society, 2015, 751-759 p.Conference paper, Published 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 %.

Place, publisher, year, edition, pages
IEEE Computer Society, 2015. 751-759 p.
National Category
Communication Systems Embedded Systems
Research subject
Computer Science with specialization in Computer Communication
Identifiers
URN: urn:nbn:se:uu:diva-288527DOI: 10.1109/LCNW.2015.7365924ISI: 000380463700022ISBN: 9781467367738 (print)OAI: oai:DiVA.org:uu-288527DiVA: diva2:924222
Conference
The 10th IEEE International Workshop on Practical Issues in Building Sensor Network Applications (SenseApp'15)
Projects
ProFuN
Funder
Swedish Foundation for Strategic Research , RIT08-0065
Available from: 2016-04-28 Created: 2016-04-28 Last updated: 2016-08-24Bibliographically approved

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Elsts, AtisHassani Bijarbooneh, FarshidJacobsson, MartinSagonas, Konstantinos
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