Cost-Aware Activity Scheduling for Compressive Sleeping Wireless Sensor Networks
- Submitting institution
-
University of Cambridge
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 1902
- Type
- D - Journal article
- DOI
-
10.1109/TSP.2016.2521608
- Title of journal
- IEEE Transactions on Signal Processing
- Article number
- 9
- First page
- 2314
- Volume
- 64
- Issue
- 9
- ISSN
- 1053-587X
- Open access status
- Out of scope for open access requirements
- Month of publication
- May
- Year of publication
- 2016
- 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)
-
-
- Citation count
- 16
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This publication resulted from an EPSRC funded collaboration between Cambridge and UCL (EP/K033700/1) and several industrial collaborators, e.g., IntelliSense.io, (https://intellisense.io/) and Fujitsu Laboratories (https://www.fujitsu.com/uk/about/local/corporate/subsidiaries/fle/). Wisen Innovation (Dr. Yan Wu, email on request) has licenced the technology from Cambridge Enterprise (http://www.enterprise.cam.ac.uk/). A cost-aware activity scheduling approach for Wireless Sensor Networks to monitor parameters in a distributed network of sensors is described, where only a fraction of sensor nodes is activated to perform the sensing task. It significantly lowers energy consumption compared with conventional Nyquist sampling, i.e. increasing network lifetime, while also guaranteeing signal reconstruction accuracy.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
