The Value of Sleeping: A Rollout Algorithm for Sensor Scheduling in HMMs
David Jun, Douglas L. Jones

Citation
David Jun, Douglas L. Jones. "The Value of Sleeping: A Rollout Algorithm for Sensor Scheduling in HMMs". IEEE GlobalSIP, December, 2013.

Abstract
This paper presents a new Q-value approximation algorithm for joint sensor scheduling and MAP state estimation in hidden Markov models. The proposed algorithm is motivated by the fact that energy-constrained embedded devices spend a significant amount of time in sleep modes. To develop an adaptive sensing-resource scheduling policy, the proposed base policy computes the exact value of sleeping over an infinite time horizon. This value is incorporated to rank sensing resources, trading off sensing quality with usage cost. As the base policy is independent of the sensing modalities, the proposed method is useful in applications where observation parameters such as SNR are time-varying, and when re-optimization is not practical. For applications with significant energy constraints, the proposed policy performs better than other heuristics and achieves near optimal performance/resource trade-off, as demonstrated in a long-term energy-constrained wildlife monitoring application.

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Citation formats

• HTML

  David Jun, Douglas L. Jones. <a
  href="http://www.terraswarm.org/pubs/103.html"
  >The Value of Sleeping: A Rollout Algorithm for Sensor
  Scheduling in HMMs</a>, IEEE GlobalSIP, December, 2013.

• Plain text

  David Jun, Douglas L. Jones. "The Value of Sleeping: A
  Rollout Algorithm for Sensor Scheduling in HMMs". IEEE
  GlobalSIP, December, 2013.

• BibTeX

  @inproceedings{JunJones13_ValueOfSleepingRolloutAlgorithmForSensorSchedulingIn,
      author = {David Jun and Douglas L. Jones},
      title = {The Value of Sleeping: A Rollout Algorithm for
                Sensor Scheduling in HMMs},
      booktitle = {IEEE GlobalSIP},
      month = {December},
      year = {2013},
      abstract = {This paper presents a new Q-value approximation
                algorithm for joint sensor scheduling and MAP
                state estimation in hidden Markov models. The
                proposed algorithm is motivated by the fact that
                energy-constrained embedded devices spend a
                significant amount of time in sleep modes. To
                develop an adaptive sensing-resource scheduling
                policy, the proposed base policy computes the
                exact value of sleeping over an infinite time
                horizon. This value is incorporated to rank
                sensing resources, trading off sensing quality
                with usage cost. As the base policy is independent
                of the sensing modalities, the proposed method is
                useful in applications where observation
                parameters such as SNR are time-varying, and when
                re-optimization is not practical. For applications
                with significant energy constraints, the proposed
                policy performs better than other heuristics and
                achieves near optimal performance/resource
                trade-off, as demonstrated in a long-term
                energy-constrained wildlife monitoring application.},
      URL = {http://terraswarm.org/pubs/103.html}
  }
  

Posted by Mila MacBain on 22 Aug 2013.