Collaborative Sensor Caching via Sequential Compressed Sensing
- Resource Type
- Conference
- Authors
- Yang, Yi-Jen; Yang, Ming-Hsun; Hong, Y.-W. Peter; Wu, Jwo-Yuh
- Source
- ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Acoustics, Speech and Signal Processing (ICASSP), ICASSP 2019 - 2019 IEEE International Conference on. :4579-4583 May, 2019
- Subject
- Bioengineering
Communication, Networking and Broadcast Technologies
Signal Processing and Analysis
Collaboration
Wireless sensor networks
Reconstruction algorithms
Compressed sensing
Cache storage
Mathematical model
Sensors
Caching
wireless sensor networks
compressed sensing
alternating direction method of multipliers
- Language
- ISSN
- 2379-190X
This work proposes a collaborative sensor caching and data reconstruction method based on the sequential compressed sensing framework. Here, multiple caches are assumed to exist in the wireless sensor network to store the most recent data gathered from sensors within their respective coverage areas. To reduce the cache size and the data-acquisition overhead, each cache accesses measurements only from a small subset of sensors. This work proposes a collaborative sparse-signal reconstruction method that exploits the presence of sensors simultaneously accessible by multiple caches as anchor nodes to introduce dependency in the reconstruction. The reconstruction is based on the use of the alternating direction method of multipliers (ADMM), which enables distributed implementation of the algorithm. Simulations are provided to demonstrate the effectiveness of the proposed scheme.