A task scheduler framework for self-powered wireless sensors.
The cost and inconvenience of cabling is a factor limiting widespread use of intelligent sensors. Recent developments in short-range, low-power radio seem to provide an opening to this problem, making development of wireless sensors feasible. However, for these sensors the energy availability is a main concern. The common solution is either to use a battery or to harvest ambient energy. The benefit of harvested ambient energy is that the energy feeder can be considered as lasting a lifetime, thus it saves the user from concerns related to energy management. The problem is, however, the unpredictability and unsteady behavior of ambient energy sources. This becomes a main concern for sensors that run multiple tasks at different priorities. This paper proposes a new scheduler framework that enables the reliable assignment of task priorities and scheduling in sensors powered by ambient energy. The framework being based on environment parameters, virtual queues, and a state machine with transition conditions, dynamically manages task execution according to priorities. The framework is assessed in a test system powered by a solar panel. The results show the functionality of the framework and how task execution reliably is handled without violating the priority scheme that has been assigned to it.
Power Systems Laboratory, Helsinki University of Technology, P.O. Box 3000, FIN-02015 HUT, Finland.
Mikael M
MM
Nordman
D000465:Algorithms; D011211:Electric Power Supplies; D008954:Models, Biological; D013686:Telemetry / Q000295:instrumentation* / Q000379:methods*; D014159:Transducers