ProFuN TG: A tool for programming and managing performance-aware sensor network applications
2015 (English)In: IEEE 40th Local Computer Networks Conference Workshops (LCN Workshops), IEEE Computer Society, 2015, 751-759 p.Conference paper (Refereed)
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.
Communication Systems Embedded Systems
Research subject Computer Science with specialization in Computer Communication
IdentifiersURN: urn:nbn:se:uu:diva-288527DOI: 10.1109/LCNW.2015.7365924ISI: 000380463700022ISBN: 9781467367738OAI: oai:DiVA.org:uu-288527DiVA: diva2:924222
The 10th IEEE International Workshop on Practical Issues in Building Sensor Network Applications (SenseApp'15)
FunderSwedish Foundation for Strategic Research , RIT08-0065