MultiSense: proportional-share for mechanically steerable sensor networks
Steerable sensors, such as pan-tilt-zoom cameras and weather radars, expose programmable actuators to applications, which steer them to dictate the type, quality, and quantity of data they collect. Applications with different goals steer these sensors in different directions. Although being expensive to deploy and maintain, existing steerable sensor networks allow only a single application to control them due to the slow speed of their mechanical actuators. To address the problem, we design MultiSense to enable fine-grained multiplexing by (1) exposing a virtual sensor to each application and (2) optimizing the time to context-switch between virtual sensors and satisfy requests. We implement MultiSense in Xen, a widely used virtualization platform, and explore how well proportional-share scheduling, along with extensions for state restoration, request batching and merging, and anticipatory scheduling, satisfies the unique requirements of steerable sensors. We present experiments for pan-tilt-zoom cameras and weather radars that show MultiSense efficiently isolates the performance of virtual sensors, allowing concurrent applications to satisfy conflicting goals. As one example, we enable a tracking application to photograph an object moving at nearly 3mph every 23ft along its trajectory at a distance of 300ft, while supporting a security application that photographs a fixed point every 3s.
sensor camera radar virtualization