MultiSense: fine-grained multiplexing for steerable camera sensor networks

  • Authors:

  • Navin K. Sharma;David E. Irwin;Prashant J. Shenoy;Michael Zink

  • Affiliations:

  • University of Massachusetts Amherst, Amherst, MA, USA;University of Massachusetts Amherst, Amherst, MA, USA;University of Massachusetts Amherst, Amherst, MA, USA;University of Massachusetts Amherst, Amherst, MA, USA

  • Venue:
  • MMSys '11 Proceedings of the second annual ACM conference on Multimedia systems
  • Year:
  • 2011

Quantified Score

Hi-index 0.00

Visualization

Abstract

Steerable sensors, such as pan-tilt-zoom video cameras, expose programmable actuators to applications, which steer them in different directions based on their goals. Despite 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 (i) exposing a virtual sensor to each application and (ii) optimizing the time to context-switch between virtual sensors and satisfy requests. We implement MultiSense in Xen and explore how well proportional share scheduling, along with extensions for state restoration and request batching, satisfies the unique requirements of steerable sensors in the form of pan-tilt-zoom video cameras. We present experiments that show MultiSense efficiently isolates the performance of virtual cameras, allowing concurrent applications to satisfy conflicting goals. As one example, we enable a tracking application to photograph an object moving at nearly 3 mph every 23 ft along its trajectory at a distance of 300 ft, while supporting a security application that photographs a fixed point every 3 seconds