The value of sleeping: A rollout algorithm for sensor scheduling in HMMs

David Jun, Douglas L Jones

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish (US)
Title of host publication2013 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013 - Proceedings
Pages181-184
Number of pages4
DOIs
StatePublished - Dec 1 2013
Event2013 1st IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013 - Austin, TX, United States
Duration: Dec 3 2013Dec 5 2013

Publication series

Name2013 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013 - Proceedings

Other

Other2013 1st IEEE Global Conference on Signal and Information Processing, GlobalSIP 2013
CountryUnited States
CityAustin, TX
Period12/3/1312/5/13

ASJC Scopus subject areas

  • Information Systems
  • Signal Processing

Fingerprint Dive into the research topics of 'The value of sleeping: A rollout algorithm for sensor scheduling in HMMs'. Together they form a unique fingerprint.

Cite this