Optimal Transmission Scheduling in Data-Intensive Audio Sensor Networks

We consider the problem of scheduling audio data transmissions in data-intensive audio sensor networks for animal tracking where the sensor nodes must use WiFi duty cycling to reduce power consumption. WiFi duty cycling entails a startup cost due to probing, authentication, association, and host configuration which are significant and can reach more than 10 seconds. As such, transmission scheduling is not trivial because a naïve approach of switching on WiFi whenever there is a data to send would result in excessive energy consumption overhead. We model duty cycling after an M/G/1 queue with removable server, formulate the optimization problem considering both energy and latency overheads, and obtain the optimal
$N^{\ast}$
by which the interface should be switched on to schedule data transmission. We propose Optimal Threshold-based Transmission Scheduling (OTTS), a low-complexity algorithm for determining the optimal threshold and commencing transmission. Experiments and trace-based simulations show that OTTS can yield substantial reduction in power consumption that is controllable through an energy-latency trade-off parameter. Compared with interval-based scheduling, OTTS provides lower delay which is more significant at tighter power consumption constraints.