ProFuN TG: A Tool for Programming and Managing Performance-Aware Sensor Network Applications

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. We present ProFuN TG (Task Graph), a tool for designing sensor network applications using task graphs. ProFuN TG provides automated task mapping, sensor node firmware 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. We show that the adaptive task reallocation enabled by our approach can significantly increase application reliability while decreasing energy consumption: in a network with unreliable links, we achieve above 99.89% task-to-task PDR while keeping the maximal radio duty cycle around 2.0 %.