We investigate the problem of scheduling sensor node up-times to maximize the utility of the data they collect while operating within their resource constraints. We show that the optimal scheduling algorithm can improve data utility by more than 70% compared to naive schedules. We consider a suite of sensors with different capabilities and resource demands and represent their subsets as virtual sensors. For each virtual sensor, we calculate its optimal data fusion parameters and evaluate the sensors' performance in a given environment. The selection of virtual sensors best suited to collect data in a given environment can be modeled as an Integer Linear programming problem, and we study three different algorithms to solve the problem efficiently. We evaluate the performance of virtual sensor scheduling algorithms by extensive simulation. We show that even though the naive greedy scheduling approaches work well in some scenarios, none of them are able to match our best scheduling algorithm consistently, under varying environmental conditions and sensor resources.

We describe our current work towards a framework that establishes a hierarchy of devices (sensors and actuators) within a wireless multimedia node and uses frequent sampling of cheaper devices to trigger the activation of more energy-hungry devices. Within this framework, we consider the suitability of servos for Wireless Multimedia Sensor Networks (WMSNs) by examining their functional characteristics and energy consumption [2].

This paper considers the use of servo-mechanisms as part of a tightly integrated homogeneous wireless multimedia sensor network (WMSN). We describe the design of our second generation WMSN node platform, which has increased image resolution, in-built audio sensors, PIR sensors, and servomechanisms. These devices have a wide disparity in their energy consumption and in the information quality they return. As a result, we propose a framework that establishes a hierarchy of devices (sensors and actuators) within the node and uses frequent sampling of cheaper devices to trigger the activation of more energy-hungry devices. Within this framework, we consider the suitability of servos for WMSNs by examining the functional characteristics and by measuring the energy consumption of 2 analog and 2 digital servos, in order to determine their impact on overall node energy cost. We also implement a simple version of our hierarchical sampling framework to evaluate the energy consumption of servos relative to other node components. The evaluation results show that: (1) the energy consumption of servos is small relative to audio/image signal processing energy cost in WMSN nodes; (2) digital servos do not necessarily consume as much energy as is currently believed; and (3) the energy cost per degree panning is lower for larger panning angles.