Towards data-centric control of sensor networks through Bayesian dynamic linear modelling
- Submitting institution
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University of St Andrews
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 251740272
- Type
- E - Conference contribution
- DOI
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10.1109/SASO.2015.14
- Title of conference / published proceedings
- 2015 IEEE 9th International Conference on Self-Adaptive and Self-Organizing Systems (SASO)
- First page
- 61
- Volume
- -
- Issue
- -
- ISSN
- 1949-3673
- Open access status
- Out of scope for open access requirements
- Month of publication
- October
- Year of publication
- 2015
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
1
- Research group(s)
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B - Systems
- Citation count
- 3
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper provides the statistical underpinnings for the distributed optimisation of control in sensor networks, which is essential for improving sensor lifetimes and system robustness to failures. This enormously improves the ability of systems to make scheduling and other decisions relative to the ad hoc techniques in widespread use, as well as providing a well-founded basis for exploring other techniques.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
