Find the weakest link : statistical analysis on wireless sensor network link-quality metrics
- Submitting institution
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Kingston University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 11-55-1384
- Type
- D - Journal article
- DOI
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10.1109/MVT.2014.2333693
- Title of journal
- IEEE Vehicular Technology Magazine
- Article number
- -
- First page
- 28
- Volume
- 9
- Issue
- -
- ISSN
- 1556-6072
- Open access status
- Out of scope for open access requirements
- Month of publication
- -
- Year of publication
- 2014
- URL
-
-
- Supplementary information
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- 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
-
-
- Research group(s)
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- Citation count
- 15
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This study investigates two prominent link-quality metrics—received signal strength indication (RSSI) and link-quality indication (LQI). The evaluation reported in this article is based on a series of WSN testbeds in real life scenarios. The paper was originally submitted to the WWRF (Wireless World Research Forum) meeting in 2014 and subsequently selected as one of the best 4 scientific papers to be published in the IEEE VT Magazine. This paper has contributed to a long lasting collaboration with the WWRF, including funding to lead a related work group (e/m-Health and Wearables) in the Forum.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -