Collaborative sparse signal recovery in hierarchical wireless sensor networks
Document Type
Conference Proceeding
Publication Date
12-1-2009
Abstract
This paper investigates the design choices and implementation schemes for information fusion among cluster heads in a large-scale hierarchical wireless sensor network. Two mainissues addressed are: whether to choose centralized processing with aid of a fusion center or decentralized collaboration among cluster heads, and for the latter choice, how to collaborate. Based on a sparse signal recovery problem arising from an environmental monitoring application, we propose a decentralized collaborative decision-making algorithm for cluster heads, and compare it with the centralized scheme. Our observation is: when the number of sensors within each cluster is quite large to induce a large amount of data, and the cluster heads are subject to multi-hop communications due to limited communication range, the collaborative algorithm is superior to the centralized one in terms of communication load and energy efffciency. © 2009 IEEE.
Publication Title
CAMSAP 2009 - 2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing
Recommended Citation
Ling, Q.,
&
Tian, Z.
(2009).
Collaborative sparse signal recovery in hierarchical wireless sensor networks.
CAMSAP 2009 - 2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 125-128.
http://doi.org/10.1109/CAMSAP.2009.5413322
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/10355
