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MultiSense: proportional-share for mechanically steerable sensor networks

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Abstract

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 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 s.

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Notes

  1. One could compare a weather radar to a more complicated camera that works at a lower frequency.

  2. The example assumes the points are along a circle with radius 100 ft with camera’s lens as its center.

  3. Our example assumes that the object’s trajectory is along a circle of radius 300 ft with the camera’s lens as its center.

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Acknowledgments

We would like to thank the anonymous reviewers for their insightful comments that improved this paper. This work was supported in part by NSF grants CNS-1117221, OCI-1032765, CNS-0916577, and CNS-0855128.

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Authors and Affiliations

  1. University of Massachusetts, Amherst, USA

    Navin Sharma, David Irwin, Michael Zink & Prashant Shenoy

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  1. Navin Sharma
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  2. David Irwin
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  3. Michael Zink
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  4. Prashant Shenoy
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Correspondence to Navin Sharma.

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Communicated by T. Plagemann.

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Sharma, N., Irwin, D., Zink, M. et al. MultiSense: proportional-share for mechanically steerable sensor networks. Multimedia Systems 18, 425–444 (2012). https://doi.org/10.1007/s00530-012-0292-y

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