Title :
Transform-Based Distributed Data Gathering
Author :
Shen, Godwin ; Ortega, Antonio
Author_Institution :
Dept. of Electr. Eng., Univ. of Southern California, Los Angeles, CA, USA
fDate :
7/1/2010 12:00:00 AM
Abstract :
A general class of unidirectional transforms is presented that can be computed in a distributed manner along an arbitrary routing tree. Additionally, we provide a set of conditions under which these transforms are invertible. These transforms can be computed as data is routed towards the collection (or sink) node in the tree and exploit data correlation between nodes in the tree. Moreover, when used in wireless sensor networks, these transforms can also leverage data received at nodes via broadcast wireless communications. Various constructions of unidirectional transforms are also provided for use in data gathering in wireless sensor networks. New wavelet transforms are also proposed which provide significant improvements over existing unidirectional transforms.
Keywords :
data analysis; data compression; telecommunication network routing; telecommunication network topology; wavelet transforms; wireless sensor networks; arbitrary routing tree; broadcast wireless communications; data compression; data correlation; transform-based distributed data gathering; unidirectional transforms; wavelet transforms; wireless sensor networks; Data compression; wavelet transforms; wireless sensor networks;
Journal_Title :
Signal Processing, IEEE Transactions on
DOI :
10.1109/TSP.2010.2047640